Capturing text from rendered documents using supplement information

ABSTRACT

A system for processing a text capture operation is described. The system receives text captured from a rendered document in the text capture operation. The system also receives supplemental information distinct from the captured text. The system determines an action to perform in response to the text capture operation based upon both the captured text and the supplemental information.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.12/542,816, filed Aug. 18, 2009, which is a continuation application ofprior U.S. application Ser. No. 11/096,704, filed Apr. 1, 2005 andissued as U.S. Pat. No. 7,599,580 on Oct. 6, 2009. U.S. application Ser.No. 12/542,816 and U.S. Pat. No. 7,599,580 are incorporated herein byreference. Prior U.S. application Ser. No. 11/096,704 is acontinuation-in-part of U.S. patent application Ser. No. 11/004,637filed on Dec. 3, 2004, which is hereby incorporated by reference.

This application is related to, and incorporates by reference in theirentirety, the following U.S. Patent Applications: U.S. patentapplication Ser. No. 11/097,961, filed Apr. 1, 2005, U.S. patentapplication Ser. No. 11/097,093, filed Apr. 1, 2005, U.S. patentapplication Ser. No. 11/098,038, filed Apr. 1, 2005 and issued on Oct.6, 2009 as U.S. Pat. No. 7,599,844, U.S. patent application Ser. No.11/098,014, filed Apr. 1, 2005 and issued on Sep. 13, 2011 as U.S. Pat.No. 8,019,648, U.S. patent application Ser. No. 11/097,103, filed Apr.1, 2005 and issued on Sep. 29, 2009 as U.S. Pat. No. 7,596,269, U.S.patent application Ser. No. 11/097,828, filed Apr. 1, 2005 and issued onJun. 22, 2010 as U.S. Pat. No. 7,742,953, U.S. patent application Ser.No. 11/097,981, filed Apr. 1, 2005 and issued on Oct. 20, 2009 as U.S.Pat. No. 7,606,741, U.S. patent application Ser. No. 11/097,089, filedApr. 1, 2005 and issued on Jul. 3, 2012 as U.S. Pat. No. 8,214,387, U.S.patent application Ser. No. 11/097,835, filed Apr. 1, 2005 and issued onNov. 9, 2010 as U.S. Pat. No. 7,831,912, U.S. patent application Ser.No. 11/098,016, filed Apr. 1, 2005 and issued on Sep. 2, 2008 as U.S.Pat. No. 7,421,155, U.S. patent application Ser. No. 11/097,828, filedApr. 1, 2005 and issued on Jun. 22, 2010 as U.S. Pat. No. 7,742,953,U.S. patent application Ser. No. 11/097,833, filed Apr. 1, 2005, U.S.patent application Ser. No. 11/097,836, filed Apr. 1, 2005, and U.S.patent application Ser. No. 11/098,042, filed Apr. 1, 2005 and issued onSep. 22, 2009 as U.S. Pat. No. 7,593,605.

This application claims priority to, and incorporates by reference intheir entirety, the following U.S. Provisional patent applications:Application No. 60/559,226 filed on Apr. 1, 2004, Application No.60/558,893 filed on Apr. 1, 2004, Application No. 60/558,968 filed onApr. 1, 2004, Application No. 60/558,867 filed on Apr. 1, 2004,Application No. 60/559,278 filed on Apr. 1, 2004, Application No.60/559,279 filed on Apr. 1, 2004, Application No. 60/559,265 filed onApr. 1, 2004, Application No. 60/559,277 filed on Apr. 1, 2004,Application No. 60/558,969 filed on Apr. 1, 2004, Application No.60/558,892 filed on Apr. 1, 2004, Application No. 60/558,760 filed onApr. 1, 2004, Application No. 60/558,717 filed on Apr. 1, 2004,Application No. 60/558,499 filed on Apr. 1, 2004, Application No.60/558,370 filed on Apr. 1, 2004, Application No. 60/558,789 filed onApr. 1, 2004, Application No. 60/558,791 filed on Apr. 1, 2004,Application No. 60/558,527 filed on Apr. 1, 2004, Application No.60/559,125 filed on Apr. 2, 2004, Application No. 60/558,909 filed onApr. 2, 2004, Application No. 60/559,033 filed on Apr. 2, 2004,Application No. 60/559,127 filed on Apr. 2, 2004, Application No.60/559,087 filed on Apr. 2, 2004, Application No. 60/559,131 filed onApr. 2, 2004, Application No. 60/559,766 filed on Apr. 6, 2004,Application No. 60/561,768 filed on Apr. 12, 2004, Application No.60/563,520 filed on Apr. 19, 2004, Application No. 60/563,485 filed onApr. 19, 2004, Application No. 60/564,688 filed on Apr. 23, 2004,Application No. 60/564,846 filed on Apr. 23, 2004, Application No.60/556,667 filed on Apr. 30, 2004, Application No. 60/571,381 filed onMay 14, 2004, Application No. 60/571,560 filed on May 14, 2004,Application No. 60/571,715 filed on May 17, 2004, Application No.60/589,203 filed on Jul. 19, 2004, Application No. 60/589,201 filed onJul. 19, 2004, Application No. 60/589,202 filed on Jul. 19, 2004,Application No. 60/598,821 filed on Aug. 2, 2004, Application No.60/602,956 filed on Aug. 18, 2004, Application No. 60/602,925 filed onAug. 18, 2004, Application No. 60/602,947 filed on Aug. 18, 2004,Application No. 60/602,897 filed on Aug. 18, 2004, Application No.60/602,896 filed on Aug. 18, 2004, Application No. 60/602,930 filed onAug. 18, 2004, Application No. 60/602,898 filed on Aug. 18, 2004,Application No. 60/603,466 filed on Aug. 19, 2004, Application No.60/603,082 filed on Aug. 19, 2004, Application No. 60/603,081 filed onAug. 19, 2004, Application No. 60/603,498 filed on Aug. 20, 2004,Application No. 60/603,358 filed on Aug. 20, 2004, Application No.60/604,103 filed on Aug. 23, 2004, Application No. 60/604,098 filed onAug. 23, 2004, Application No. 60/604,100 filed on Aug. 23, 2004,Application No. 60/604,102 filed on Aug. 23, 2004, Application No.60/605,229 filed on Aug. 27, 2004, Application No. 60/605,105 filed onAug. 27, 2004, Application No. 60/613,243 filed on Sep. 27, 2004,Application No. 60/613,628 filed on Sep. 27, 2004, Application No.60/613,632 filed on Sep. 27, 2004, Application No. 60/613,589 filed onSep. 27, 2004, Application No. 60/613,242 filed on Sep. 27, 2004,Application No. 60/613,602 filed on Sep. 27, 2004, Application No.60/613,340 filed on Sep. 27, 2004, Application No. 60/613,634 filed onSep. 27, 2004, Application No. 60/613,461 filed on Sep. 27, 2004,Application No. 60/613,455 filed on Sep. 27, 2004, Application No.60/613,460 filed on Sep. 27, 2004, Application No. 60/613,400 filed onSep. 27, 2004, Application No. 60/613,456 filed on Sep. 27, 2004,Application No. 60/613,341 filed on Sep. 27, 2004, Application No.60/613,361 filed on Sep. 27, 2004, Application No. 60/613,454 filed onSep. 27, 2004, Application No. 60/613,339 filed on Sep. 27, 2004,Application No. 60/613,633 filed on Sep. 27, 2004, Application No.60/615,378 filed on Oct. 1, 2004, Application No. 60/615,112 filed onOct. 1, 2004, Application No. 60/615,538 filed on Oct. 1, 2004,Application No. 60/617,122 filed on Oct. 7, 2004, Application No.60/622,906 filed on Oct. 28, 2004, Application No. 60/633,452 filed onDec. 6, 2004, Application No. 60/633,678 filed on Dec. 6, 2004,Application No. 60/633,486 filed on Dec. 6, 2004, Application No.60/633,453 filed on Dec. 6, 2004, Application No. 60/634,627 filed onDec. 9, 2004, Application No. 60/634,739 filed on Dec. 9, 2004,Application No. 60/647,684 filed on Jan. 26, 2005, Application No.60/648,746 filed on Jan. 31, 2005, Application No. 60/653,372 filed onFeb. 15, 2005, Application No. 60/653,663 filed on Feb. 16, 2005,Application No. 60/653,669 filed on Feb. 16, 2005, Application No.60/653,899 filed on Feb. 16, 2005, Application No. 60/653,679 filed onFeb. 16, 2005, Application No. 60/653,847 filed on Feb. 16, 2005,Application No. 60/654,379 filed on Feb. 17, 2005, Application No.60/654,368 filed on Feb. 18, 2005, Application No. 60/654,326 filed onFeb. 18, 2005, Application No. 60/654,196 filed on Feb. 18, 2005,Application No. 60/655,279 filed on Feb. 22, 2005, Application No.60/655,280 filed on Feb. 22, 2005, Application No. 60/655,987 filed onFeb. 22, 2005, Application No. 60/655,697 filed on Feb. 22, 2005,Application No. 60/655,281 filed on Feb. 22, 2005, and Application No.60/657,309 filed on Feb. 28, 2005.

TECHNICAL FIELD

The described technology is directed to the field of documentprocessing.

BACKGROUND

Paper documents have an enduring appeal, as can be seen by theproliferation of paper documents in the computer age. It has never beeneasier to print and publish paper documents than it is today. Paperdocuments prevail even though electronic documents are easier toduplicate, transmit, search and edit.

Given the popularity of paper documents and the advantages of electronicdocuments, it would be useful to combine the benefits of both.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a data flow diagram that illustrates the flow of informationin one embodiment of the system.

FIG. 2 is a component diagram of components included in a typicalimplementation of the system in the context of a typical operatingenvironment.

FIG. 3 is a block diagram of an embodiment of a scanner.

FIG. 4 is a block diagram showing some of the components typicallyincorporated in at least some of the computer systems and other devicesused by the system.

FIG. 5 is a data flow diagram showing a typical manner in which thesystem uses context information.

DETAILED DESCRIPTION Overview

A system for capturing text from rendered documents using supplementalinformation (“the system”) is described.

In some embodiments, the system captures text from a rendered documentand associates some action, data, or functionality with that capture.Section 13 introduces the idea of using supplemental information aboutthe circumstances under which a capture is performed, together withsupplemental information about the user who performed the capture(sometimes collectively called “context”), as well as the data actuallycaptured, to interpret the meaning of the capture and to determine theassociations and actions that should appropriately follow. This is incontrast, for example, to conventional web search engines, whichtypically maintain very little context information from one searchinvocation to another, and know little about the circumstances underwhich the search query was performed.

By considering context, the system can reduce many degrees ofuncertainty in its processes. For example, if the captured data couldhave come from any of several documents, the system can utilize thecontext to discard many that would be highly unlikely and helpprioritize those that remain. Similarly, if the source of a capture isrecognized but there are many actions that the user may wish to take asa result, the context can be a valuable aid in deciding which one shouldbe the default. The uses to which the system puts context in variousembodiments are discussed in more detail below.

Part I Introduction

1. Nature of the System

For every paper document that has an electronic counterpart, thereexists a discrete amount of information in the paper document that canidentify the electronic counterpart. In some embodiments, the systemuses a sample of text captured from a paper document, for example usinga handheld scanner, to identify and locate an electronic counterpart ofthe document. In most cases, the amount of text needed by the facilityis very small in that a few words of text from a document can oftenfunction as an identifier for the paper document and as a link to itselectronic counterpart. In addition, the system may use those few wordsto identify not only the document, but also a location within thedocument.

Thus, paper documents and their digital counterparts can be associatedin many useful ways using the system discussed herein.

1.1. A Quick Overview of the Future

Once the system has associated a piece of text in a paper document witha particular digital entity has been established, the system is able tobuild a huge amount of functionality on that association.

It is increasingly the case that most paper documents have an electroniccounterpart that is accessible on the World Wide Web or from some otheronline database or document corpus, or can be made accessible, such asin response to the payment of a fee or subscription. At the simplestlevel, then, when a user scans a few words in a paper document, thesystem can retrieve that electronic document or some part of it, ordisplay it, email it to somebody, purchase it, print it or post it to aweb page. As additional examples, scanning a few words of a book that aperson is reading over breakfast could cause the audio-book version inthe person's car to begin reading from that point when s/he startsdriving to work, or scanning the serial number on a printer cartridgecould begin the process of ordering a replacement.

The system implements these and many other examples of “paper/digitalintegration” without requiring changes to the current processes ofwriting, printing and publishing documents, giving such conventionalrendered documents a whole new layer of digital functionality.

1.2. Terminology

A typical use of the system begins with using an optical scanner to scantext from a paper document, but it is important to note that othermethods of capture from other types of document are equally applicable.The system is therefore sometimes described as scanning or capturingtext from a rendered document, where those terms are defined as follows:

A rendered document is a printed document or a document shown on adisplay or monitor. It is a document that is perceptible to a human,whether in permanent form or on a transitory display.

Scanning or capturing is the process of systematic examination to obtaininformation from a rendered document. The process may involve opticalcapture using a scanner or camera (for example a camera in a cellphone),or it may involve reading aloud from the document into an audio capturedevice or typing it on a keypad or keyboard. For more examples, seeSection 15.

2. Introduction to the System

This section describes some of the devices, processes and systems thatconstitute a system for paper/digital integration. In variousembodiments, the system builds a wide variety of services andapplications on this underlying core that provides the basicfunctionality.

2.1. The Processes

FIG. 1 is a data flow diagram that illustrates the flow of informationin one embodiment of the core system. Other embodiments may not use allof the stages or elements illustrated here, while some will use manymore.

Text from a rendered document is captured 100, typically in optical formby an optical scanner or audio form by a voice recorder, and this imageor sound data is then processed 102, for example to remove artifacts ofthe capture process or to improve the signal-to-noise ratio. Arecognition process 104 such as OCR, speech recognition, orautocorrelation then converts the data into a signature, comprised insome embodiments of text, text offsets, or other symbols. Alternatively,the system performs an alternate form of extracting document signaturefrom the rendered document. The signature represents a set of possibletext transcriptions in some embodiments. This process may be influencedby feedback from other stages, for example, if the search process andcontext analysis 110 have identified some candidate documents from whichthe capture may originate, thus narrowing the possible interpretationsof the original capture.

A post-processing 106 stage may take the output of the recognitionprocess and filter it or perform such other operations upon it as may beuseful. Depending upon the embodiment implemented, it may be possible atthis stage to deduce some direct actions 107 to be taken immediatelywithout reference to the later stages, such as where a phrase or symbolhas been captured which contains sufficient information in itself toconvey the user's intent. In these cases no digital counterpart documentneed be referenced, or even known to the system.

Typically, however, the next stage will be to construct a query 108 or aset of queries for use in searching. Some aspects of the queryconstruction may depend on the search process used and so cannot beperformed until the next stage, but there will typically be someoperations, such as the removal of obviously misrecognized or irrelevantcharacters, which can be performed in advance.

The query or queries are then passed to the search and context analysisstage 110. Here, the system optionally attempts to identify the documentfrom which the original data was captured. To do so, the systemtypically uses search indices and search engines 112, knowledge aboutthe user 114 and knowledge about the user's context or the context inwhich the capture occurred 116. Search engine 112 may employ and/orindex information specifically about rendered documents, about theirdigital counterpart documents, and about documents that have a web(internet) presence). It may write to, as well as read from, many ofthese sources and, as has been mentioned, it may feed information intoother stages of the process, for example by giving the recognitionsystem 104 information about the language, font, rendering and likelynext words based on its knowledge of the candidate documents.

In some circumstances the next stage will be to retrieve 120 a copy ofthe document or documents that have been identified. The sources of thedocuments 124 may be directly accessible, for example from a localfiling system or database or a web server, or they may need to becontacted via some access service 122 which might enforceauthentication, security or payment or may provide other services suchas conversion of the document into a desired format.

Applications of the system may take advantage of the association ofextra functionality or data with part or all of a document. For example,advertising applications discussed in Section 10.4 may use anassociation of particular advertising messages or subjects with portionsof a document. This extra associated functionality or data can bethought of as one or more overlays on the document, and is referred toherein as “markup”. The next stage of the process 130, then, is toidentify any markup relevant to the captured data. Such markup may beprovided by the user, the originator, or publisher of the document, orsome other party, and may be directly accessible from some source 132 ormay be generated by some service 134. In various embodiments, markup canbe associated with, and apply to, a rendered document and/or the digitalcounterpart to a rendered document, or to groups of either or both ofthese documents.

Lastly, as a result of the earlier stages, some actions may be taken140. These may be default actions such as simply recording theinformation found, they may be dependent on the data or document, orthey may be derived from the markup analysis. Sometimes the action willsimply be to pass the data to another system. In some cases the variouspossible actions appropriate to a capture at a specific point in arendered document will be presented to the user as a menu on anassociated display, for example on a local display 332, on a computerdisplay 212 or a mobile phone or PDA display 216. If the user doesn'trespond to the menu, the default actions can be taken.

2.2. The Components

FIG. 2 is a component diagram of components included in a typicalimplementation of the system in the context of a typical operatingenvironment. As illustrated, the operating environment includes one ormore optical scanning capture devices 202 or voice capture devices 204.In some embodiments, the same device performs both functions. Eachcapture device is able to communicate with other parts of the systemsuch as a computer 212 and a mobile station 216 (e.g., a mobile phone orPDA) using either a direct wired or wireless connection, or through thenetwork 220, with which it can communicate using a wired or wirelessconnection, the latter typically involving a wireless base station 214.In some embodiments, the capture device is integrated in the mobilestation, and optionally shares some of the audio and/or opticalcomponents used in the device for voice communications andpicture-taking.

Computer 212 may include a memory containing computer executableinstructions for processing an order from scanning devices 202 and 204.As an example, an order can include an identifier (such as a serialnumber of the scanning device 202/204 or an identifier that partially oruniquely identifies the user of the scanner), scanning contextinformation (e.g., time of scan, location of scan, etc.) and/or scannedinformation (such as a text string) that is used to uniquely identifythe document being scanned. In alternative embodiments, the operatingenvironment may include more or less components.

Also available on the network 220 are search engines 232, documentsources 234, user account services 236, markup services 238 and othernetwork services 239. The network 220 may be a corporate intranet, thepublic Internet, a mobile phone network or some other network, or anyinterconnection of the above.

Regardless of the manner by which the devices are coupled to each other,they may all may be operable in accordance with well-known commercialtransaction and communication protocols (e.g., Internet Protocol (IP)).In various embodiments, the functions and capabilities of scanningdevice 202, computer 212, and mobile station 216 may be wholly orpartially integrated into one device. Thus, the terms scanning device,computer, and mobile station can refer to the same device depending uponwhether the device incorporates functions or capabilities of thescanning device 202, computer 212 and mobile station 216. In addition,some or all of the functions of the search engines 232, document sources234, user account services 236, markup services 238 and other networkservices 239 may be implemented on any of the devices and/or otherdevices not shown.

2.3. The Capture Device

As described above, the capture device may capture text using an opticalscanner that captures image data from the rendered document, or using anaudio recording device that captures a user's spoken reading of thetext, or other methods. Some embodiments of the capture device may alsocapture images, graphical symbols and icons, etc., including machinereadable codes such as barcodes. The device may be exceedingly simple,consisting of little more than the transducer, some storage, and a datainterface, relying on other functionality residing elsewhere in thesystem, or it may be a more full-featured device. For illustration, thissection describes a device based around an optical scanner and with areasonable number of features.

Scanners are well known devices that capture and digitize images. Anoffshoot of the photocopier industry, the first scanners were relativelylarge devices that captured an entire document page at once. Recently,portable optical scanners have been introduced in convenient formfactors, such as a pen-shaped handheld device.

In some embodiments, the portable scanner is used to scan text,graphics, or symbols from rendered documents. The portable scanner has ascanning element that captures text, symbols, graphics, etc, fromrendered documents. In addition to documents that have been printed onpaper, in some embodiments, rendered documents include documents thathave been displayed on a screen such as a CRT monitor or LCD display.

FIG. 3 is a block diagram of an embodiment of a scanner 302. The scanner302 comprises an optical scanning head 308 to scan information fromrendered documents and convert it to machine-compatible data, and anoptical path 306, typically a lens, an aperture or an image conduit toconvey the image from the rendered document to the scanning head. Thescanning head 308 may incorporate a Charge-Coupled Device (CCD), aComplementary Metal Oxide Semiconductor (CMOS) imaging device, or anoptical sensor of another type.

A microphone 310 and associated circuitry convert the sound of theenvironment (including spoken words) into machine-compatible signals,and other input facilities exist in the form of buttons, scroll-wheelsor other tactile sensors such as touch-pads 314.

Feedback to the user is possible through a visual display or indicatorlights 332, through a loudspeaker or other audio transducer 334 andthrough a vibrate module 336.

The scanner 302 comprises logic 326 to interact with the various othercomponents, possibly processing the received signals into differentformats and/or interpretations. Logic 326 may be operable to read andwrite data and program instructions stored in associated storage 330such as RAM, ROM, flash, or other suitable memory. It may read a timesignal from the clock unit 328. The scanner 302 also includes aninterface 316 to communicate scanned information and other signals to anetwork and/or an associated computing device. In some embodiments, thescanner 302 may have an on-board power supply 332. In other embodiments,the scanner 302 may be powered from a tethered connection to anotherdevice, such as a Universal Serial Bus (USB) connection.

As an example of one use of scanner 302, a reader may scan some textfrom a newspaper article with scanner 302. The text is scanned as abit-mapped image via the scanning head 308. Logic 326 causes thebit-mapped image to be stored in memory 330 with an associatedtime-stamp read from the clock unit 328. Logic 326 may also performoptical character recognition (OCR) or other post-scan processing on thebit-mapped image to convert it to text. Logic 326 may optionally extracta signature from the image, for example by performing a convolution-likeprocess to locate repeating occurrences of characters, symbols orobjects, and determine the distance or number of other characters,symbols, or objects between these repeated elements. The reader may thenupload the bit-mapped image (or text or other signature, if post-scanprocessing has been performed by logic 326) to an associated computervia interface 316.

As an example of another use of scanner 302, a reader may capture sometext from an article as an audio file by using microphone 310 as anacoustic capture port. Logic 326 causes audio file to be stored inmemory 328. Logic 326 may also perform voice recognition or otherpost-scan processing on the audio file to convert it to text. As above,the reader may then upload the audio file (or text produced by post-scanprocessing performed by logic 326) to an associated computer viainterface 316.

Part II Overview of the Areas of the Core System

As paper-digital integration becomes more common, there are many aspectsof existing technologies that can be changed to take better advantage ofthis integration, or to enable it to be implemented more effectively.This section highlights some of those issues.

3. Search

Searching a corpus of documents, even so large a corpus as the WorldWide Web, has become commonplace for ordinary users, who use a keyboardto construct a search query which is sent to a search engine. Thissection and the next discuss the aspects of both the construction of aquery originated by a capture from a rendered document, and the searchengine that handles such a query.

3.1. Scan/Speak/Type as Search Query

Use of the described system typically starts with a few words beingcaptured from a rendered document using any of several methods,including those mentioned in Section 1.2 above. Where the input needssome interpretation to convert it to text, for example in the case ofOCR or speech input, there may be end-to-end feedback in the system sothat the document corpus can be used to enhance the recognition process.End-to-end feedback can be applied by performing an approximation of therecognition or interpretation, identifying a set of one or morecandidate matching documents, and then using information from thepossible matches in the candidate documents to further refine orrestrict the recognition or interpretation. Candidate documents can beweighted according to their probable relevance (for example, based onthen number of other users who have scanned in these documents, or theirpopularity on the Internet), and these weights can be applied in thisiterative recognition process.

3.2. Short Phrase Searching

Because the selective power of a search query based on a few words isgreatly enhanced when the relative positions of these words are known,only a small amount of text need be captured for the system to identifythe text's location in a corpus. Most commonly, the input text will be acontiguous sequence of words, such as a short phrase.

3.2.1. Finding Document and Location in Document from Short Capture

In addition to locating the document from which a phrase originates, thesystem can identify the location in that document and can take actionbased on this knowledge.

3.2.2. Other Methods of Finding Location

The system may also employ other methods of discovering the document andlocation, such as by using watermarks or other special markings on therendered document.

3.3. Incorporation of Other Factors in Search Query

In addition to the captured text, other factors (i.e., information aboutuser identity, profile, and context) may form part of the search query,such as the time of the capture, the identity and geographical locationof the user, knowledge of the user's habits and recent activities, etc.

The document identity and other information related to previouscaptures, especially if they were quite recent, may form part of asearch query.

The identity of the user may be determined from a unique identifierassociated with a capturing device, and/or biometric or othersupplemental information (speech patterns, fingerprints, etc.).

3.4. Knowledge of Nature of Unreliability in Search Query (OCR ErrorsEtc)

The search query can be constructed taking into account the types oferrors likely to occur in the particular capture method used. Oneexample of this is an indication of suspected errors in the recognitionof specific characters; in this instance a search engine may treat thesecharacters as wildcards, or assign them a lower priority.

3.5. Local Caching of Index for Performance/Offline Use

Sometimes the capturing device may not be in communication with thesearch engine or corpus at the time of the data capture. For thisreason, information helpful to the offline use of the device may bedownloaded to the device in advance, or to some entity with which thedevice can communicate. In some cases, all or a substantial part of anindex associated with a corpus may be downloaded. This topic isdiscussed further in Section 15.3.

3.6. Queries, in Whatever Form, May be Recorded and Acted on Later

If there are likely to be delays or cost associated with communicating aquery or receiving the results, this pre-loaded information can improvethe performance of the local device, reduce communication costs, andprovide helpful and timely user feedback.

In the situation where no communication is available (the local deviceis “offline”), the queries may be saved and transmitted to the rest ofthe system at such a time as communication is restored.

In these cases it may be important to transmit a timestamp with eachquery. The time of the capture can be a significant factor in theinterpretation of the query. For example, Section 13.1 discusses theimportance of the time of capture in relation to earlier captures. It isimportant to note that the time of capture will not always be the sameas the time that the query is executed.

3.7. Parallel Searching

For performance reasons, multiple queries may be launched in response toa single capture, either in sequence or in parallel. Several queries maybe sent in response to a single capture, for example as new words areadded to the capture, or to query multiple search engines in parallel.

For example, in some embodiments, the system sends queries to a specialindex for the current document, to a search engine on a local machine,to a search engine on the corporate network, and to remote searchengines on the Internet.

The results of particular searches may be given higher priority thanthose from others.

The response to a given query may indicate that other pending queriesare superfluous; these may be cancelled before completion.

4. Paper and Search Engines

Often it is desirable for a search engine that handles traditionalonline queries also to handle those originating from rendered documents.Conventional search engines may be enhanced or modified in a number ofways to make them more suitable for use with the described system.

The search engine and/or other components of the system may create andmaintain indices that have different or extra features. The system maymodify an incoming paper-originated query or change the way the query ishandled in the resulting search, thus distinguishing thesepaper-originated queries from those coming from queries typed into webbrowsers and other sources. And the system may take different actions oroffer different options when the results are returned by the searchesoriginated from paper as compared to those from other sources. Each ofthese approaches is discussed below.

4.1. Indexing

Often, the same index can be searched using either paper-originated ortraditional queries, but the index may be enhanced for use in thecurrent system in a variety of ways.

4.1.1. Knowledge about the Paper Form

Extra fields can be added to such an index that will help in the case ofa paper-based search.

Index Entry Indicating Document Availability in Paper Form

The first example is a field indicating that the document is known toexist or be distributed in paper form. The system may give suchdocuments higher priority if the query comes from paper.

Knowledge of Popularity Paper Form

In this example statistical data concerning the popularity of paperdocuments (and, optionally, concerning sub-regions within thesedocuments)—for example the amount of scanning activity, circulationnumbers provided by the publisher or other sources, etc—is used to givesuch documents higher priority, to boost the priority of digitalcounterpart documents (for example, for browser-based queries or websearches), etc.

Knowledge of Rendered Format

Another important example may be recording information about the layoutof a specific rendering of a document.

For a particular edition of a book, for example, the index may includeinformation about where the line breaks and page breaks occur, whichfonts were used, any unusual capitalization.

The index may also include information about the proximity of otheritems on the page, such as images, text boxes, tables andadvertisements.

Use of Semantic Information in Original

Lastly, semantic information that can be deduced from the source markupbut is not apparent in the paper document, such as the fact that aparticular piece of text refers to an item offered for sale, or that acertain paragraph contains program code, may also be recorded in theindex.

4.1.2. Indexing in the Knowledge of the Capture Method

A second factor that may modify the nature of the index is the knowledgeof the type of capture likely to be used. A search initiated by anoptical scan may benefit if the index takes into account characters thatare easily confused in the OCR process, or includes some knowledge ofthe fonts used in the document. Similarly, if the query is from speechrecognition, an index based on similar-sounding phonemes may be muchmore efficiently searched. An additional factor that may affect the useof the index in the described model is the importance of iterativefeedback during the recognition process. If the search engine is able toprovide feedback from the index as the text is being captured, it cangreatly increase the accuracy of the capture.

Indexing Using Offsets

If the index is likely to be searched using theoffset-based/autocorrelation OCR methods described in Section 9, in someembodiments, the system stores the appropriate offset or signatureinformation in an index.

4.1.3. Multiple Indices

Lastly, in the described system, it may be common to conduct searches onmany indices. Indices may be maintained on several machines on acorporate network. Partial indices may be downloaded to the capturedevice, or to a machine close to the capture device. Separate indicesmay be created for users or groups of users with particular interests,habits or permissions. An index may exist for each filesystem, eachdirectory, even each file on a user's hard disk. Indexes are publishedand subscribed to by users and by systems. It will be important, then,to construct indices that can be distributed, updated, merged andseparated efficiently.

4.2. Handling the Queries

4.2.1. Knowing the Capture is from Paper

A search engine may take different actions when it recognizes that asearch query originated from a paper document. The engine might handlethe query in a way that is more tolerant to the types of errors likelyto appear in certain capture methods, for example.

It may be able to deduce this from some indicator included in the query(for example a flag indicating the nature of the capture), or it maydeduce this from the query itself (for example, it may recognize errorsor uncertainties typical of the OCR process).

Alternatively, queries from a capture device can reach the engine by adifferent channel or port or type of connection than those from othersources, and can be distinguished in that way. For example, someembodiments of the system will route queries to the search engine by wayof a dedicated gateway. Thus, the search engine knows that all queriespassing through the dedicated gateway were originated from a paperdocument.

4.2.2. Use of Context

Section 13 below describes a variety of different factors which areexternal to the captured text itself, yet which can be a significant aidin identifying a document. These include such things as the history ofrecent scans, the longer-term reading habits of a particular user, thegeographic location of a user and the user's recent use of particularelectronic documents. Such factors are referred to herein as “context”.

Some of the context may be handled by the search engine itself, and bereflected in the search results. For example, the search engine may keeptrack of a user's scanning history, and may also cross-reference thisscanning history to conventional keyboard-based queries. In such cases,the search engine maintains and uses more state information about eachindividual user than do most conventional search engines, and eachinteraction with a search engine may be considered to extend overseveral searches and a longer period of time than is typical today.

Some of the context may be transmitted to the search engine in thesearch query (Section 3.3), and may possibly be stored at the engine soas to play a part in future queries. Lastly, some of the context willbest be handled elsewhere, and so becomes a filter or secondary searchapplied to the results from the search engine.

Data-Stream Input to Search

An important input into the search process is the broader context of howthe community of users is interacting with the rendered version of thedocument—for example, which documents are most widely read and by whom.There are analogies with a web search returning the pages that are mostfrequently linked to, or those that are most frequently selected frompast search results. For further discussion of this topic, see Sections13.4 and 14.2.

4.2.3. Document Sub-Regions

The described system can emit and use not only information aboutdocuments as a whole, but also information about sub-regions ofdocuments, even down to individual words. Many existing search enginesconcentrate simply on locating a document or file that is relevant to aparticular query. Those that can work on a finer grain and identify alocation within a document will provide a significant benefit for thedescribed system.

4.3. Returning the Results

The search engine may use some of the further information it nowmaintains to affect the results returned.

The system may also return certain documents to which the user hasaccess only as a result of being in possession of the paper copy(Section 7.4).

The search engine may also offer new actions or options appropriate tothe described system, beyond simple retrieval of the text.

5. Markup, Annotations and Metadata

In addition to performing the capture-search-retrieve process, thedescribed system also associates extra functionality with a document,and in particular with specific locations or segments of text within adocument. This extra functionality is often, though not exclusively,associated with the rendered document by being associated with itselectronic counterpart. As an example, hyperlinks in a web page couldhave the same functionality when a printout of that web page is scanned.In some cases, the functionality is not defined in the electronicdocument, but is stored or generated elsewhere.

This layer of added functionality is referred to herein as “markup”.

5.1. Overlays, Static and Dynamic

One way to think of the markup is as an “overlay” on the document, whichprovides further information about—and may specify actions associatedwith—the document or some portion of it. The markup may includehuman-readable content, but is often invisible to a user and/or intendedfor machine use. Examples include options to be displayed in apopup-menu on a nearby display when a user captures text from aparticular area in a rendered document, or audio samples that illustratethe pronunciation of a particular phrase.

5.1.1. Several Layers, Possibly from Several Sources

Any document may have multiple overlays simultaneously, and these may besourced from a variety of locations. Markup data may be created orsupplied by the author of the document, or by the user, or by some otherparty.

Markup data may be attached to the electronic document or embedded init. It may be found in a conventional location (for example, in the sameplace as the document but with a different filename suffix). Markup datamay be included in the search results of the query that located theoriginal document, or may be found by a separate query to the same oranother search engine. Markup data may be found using the originalcaptured text and other capture information or contextual information,or it may be found using already-deduced information about the documentand location of the capture. Markup data may be found in a locationspecified in the document, even if the markup itself is not included inthe document.

The markup may be largely static and specific to the document, similarto the way links on a traditional html web page are often embedded asstatic data within the html document, buy markup may also be dynamicallygenerated and/or applied to a large number of documents. An example ofdynamic markup is information attached to a document that includes theup-to-date share price of companies mentioned in that document. Anexample of broadly applied markup is translation information that isautomatically available on multiple documents or sections of documentsin a particular language.

5.1.2. Personal “Plug-in” Layers

Users may also install, or subscribe to particular sources of, markupdata, thus personalizing the system's response to particular captures.

5.2. Keywords and Phrases, Trademarks and Logos

Some elements in documents may have particular “markup” or functionalityassociated with them based on their own characteristics rather thantheir location in a particular document. Examples include special marksthat are printed in the document purely for the purpose of beingscanned, as well as logos and trademarks that can link the user tofurther information about the organization concerned. The same appliesto “keywords” or “key phrases” in the text. Organizations might registerparticular phrases with which they are associated, or with which theywould like to be associated, and attach certain markup to them thatwould be available wherever that phrase was scanned.

Any word, phrase, etc. may have associated markup. For example, thesystem may add certain items to a pop-up menu (e.g., a link to an onlinebookstore) whenever the user captures the word “book,” or the title of abook, or a topic related to books. In some embodiments, of the system,digital counterpart documents or indices are consulted to determinewhether a capture occurred near the word “book,” or the title of a book,or a topic related to books—and the system behavior is modified inaccordance with this proximity to keyword elements. In the precedingexample, note that markup enables data captured from non-commercial textor documents to trigger a commercial transaction.

5.3. User-Supplied Content

5.3.1. User Comments and Annotations, Including Multimedia

Annotations are another type of electronic information that may beassociated with a document. For example, a user can attach an audio fileof his/her thoughts about a particular document for later retrieval asvoice annotations. As another example of a multimedia annotation, a usermay attach photographs of places referred to in the document. The usergenerally supplies annotations for the document but the system canassociate annotations from other sources (for example, other users in awork group may share annotations).

5.3.2. Notes from Proof-Reading

An important example of user-sourced markup is the annotation of paperdocuments as part of a proofreading, editing or reviewing process.

5.4. Third-Party Content

As mentioned earlier, markup data may often be supplied by thirdparties, such as by other readers of the document. Online discussionsand reviews are a good example, as are community-managed informationrelating to particular works, volunteer-contributed translations andexplanations.

Another example of third-party markup is that provided by advertisers.

5.5. Dynamic Markup Based on Other Users' Data Streams

By analyzing the data captured from documents by several or all users ofthe system, markup can be generated based on the activities andinterests of a community. An example might be an online bookstore thatcreates markup or annotations that tell the user, in effect, “People whoenjoyed this book also enjoyed . . . ”. The markup may be lessanonymous, and may tell the user which of the people in his/her contactlist have also read this document recently. Other examples of datastreamanalysis are included in Section 14.

5.6. Markup Based on External Events and Data Sources

Markup will often be based on external events and data sources, such asinput from a corporate database, information from the public Internet,or statistics gathered by the local operating system.

Data sources may also be more local, and in particular may provideinformation about the user's context—his/her identity, location andactivities. For example, the system might communicate with the user'smobile phone and offer a markup layer that gives the user the option tosend a document to somebody that the user has recently spoken to on thephone.

6. Authentication, Personalization and Security

In many situations, the identity of the user will be known. Sometimesthis will be an “anonymous identity”, where the user is identified onlyby the serial number of the capture device, for example. Typically,however, it is expected that the system will have a much more detailedknowledge of the user, which can be used for personalizing the systemand to allow activities and transactions to be performed in the user'sname.

6.1. User history and “Life Library”

One of the simplest and yet most useful functions that the system canperform is to keep a record for a user of the text that s/he hascaptured and any further information related to that capture, includingthe details of any documents found, the location within that documentand any actions taken as a result.

This stored history is beneficial for both the user and the system.

6.1.1. For the User

The user can be presented with a “Life Library”, a record of everythings/he has read and captured. This may be simply for personal interest,but may be used, for example, in a library by an academic who isgathering material for the bibliography of his next paper.

In some circumstances, the user may wish to make the library public,such as by publishing it on the web in a similar manner to a weblog, sothat others may see what s/he is reading and finds of interest.

Lastly, in situations where the user captures some text and the systemcannot immediately act upon the capture (for example, because anelectronic version of the document is not yet available) the capture canbe stored in the library and can be processed later, eitherautomatically or in response to a user request. A user can alsosubscribe to new markup services and apply them to previously capturedscans.

6.1.2. For the System

A record of a user's past captures is also useful for the system. Manyaspects of the system operation can be enhanced by knowing the user'sreading habits and history. The simplest example is that any scan madeby a user is more likely to come from a document that the user hasscanned in the recent past, and in particular if the previous scan waswithin the last few minutes it is very likely to be from the samedocument. Similarly, it is more likely that a document is being read instart-to-finish order. Thus, for English documents, it is also morelikely that later scans will occur farther down in the document. Suchfactors can help the system establish the location of the capture incases of ambiguity, and can also reduce the amount of text that needs tobe captured.

6.2. Scanner as Payment, Identity and Authentication Device

Because the capture process generally begins with a device of some sort,typically an optical scanner or voice recorder, this device may be usedas a key that identifies the user and authorizes certain actions.

6.2.1. Associate Scanner with Phone or Other Account

The device may be embedded in a mobile phone or in some other wayassociated with a mobile phone account. For example, a scanner may beassociated with a mobile phone account by inserting a SIM cardassociated with the account into the scanner. Similarly, the device maybe embedded in a credit card or other payment card, or have the facilityfor such a card to be connected to it. The device may therefore be usedas a payment token, and financial transactions may be initiated by thecapture from the rendered document.

6.2.2. Using Scanner Input for Authentication

The scanner may also be associated with a particular user or accountthrough the process of scanning some token, symbol or text associatedwith that user or account. In addition, scanner may be used forbiometric identification, for example by scanning the fingerprint of theuser. In the case of an audio-based capture device, the system mayidentify the user by matching the voice pattern of the user or byrequiring the user to speak a certain password or phrase.

For example, where a user scans a quote from a book and is offered theoption to buy the book from an online retailer, the user can select thisoption, and is then prompted to scan his/her fingerprint to confirm thetransaction.

See also Sections 15.5 and 15.6.

6.2.3. Secure Scanning Device

When the capture device is used to identify and authenticate the user,and to initiate transactions on behalf of the user, it is important thatcommunications between the device and other parts of the system aresecure. It is also important to guard against such situations as anotherdevice impersonating a scanner, and so-called “man in the middle”attacks where communications between the device and other components areintercepted.

Techniques for providing such security are well understood in the art;in various embodiments, the hardware and software in the device andelsewhere in the system are configured to implement such techniques.

7. Publishing Models and Elements

An advantage of the described system is that there is no need to alterthe traditional processes of creating, printing or publishing documentsin order to gain many of the system's benefits. There are reasons,though, that the creators or publishers of a document—hereafter simplyreferred to as the “publishers”—may wish to create functionality tosupport the described system.

This section is primarily concerned with the published documentsthemselves. For information about other related commercial transactions,such as advertising, see Section 10 entitled “P-Commerce”.

7.1. Electronic Companions to Printed Documents

The system allows for printed documents to have an associated electronicpresence. Conventionally publishers often ship a CD-ROM with a book thatcontains further digital information, tutorial movies and othermultimedia data, sample code or documents, or further referencematerials. In addition, some publishers maintain web sites associatedwith particular publications which provide such materials, as well asinformation which may be updated after the time of publishing, such aserrata, further comments, updated reference materials, bibliographiesand further sources of relevant data, and translations into otherlanguages. Online forums allow readers to contribute their commentsabout the publication.

The described system allows such materials to be much more closely tiedto the rendered document than ever before, and allows the discovery ofand interaction with them to be much easier for the user. By capturing aportion of text from the document, the system can automatically connectthe user to digital materials associated with the document, and moreparticularly associated with that specific part of the document.Similarly, the user can be connected to online communities that discussthat section of the text, or to annotations and commentaries by otherreaders. In the past, such information would typically need to be foundby searching for a particular page number or chapter.

An example application of this is in the area of academic textbooks(Section 17.5).

7.2. “Subscriptions” to Printed Documents

Some publishers may have mailing lists to which readers can subscribe ifthey wish to be notified of new relevant matter or when a new edition ofthe book is published. With the described system, the user can registeran interest in particular documents or parts of documents more easily,in some cases even before the publisher has considered providing anysuch functionality. The reader's interest can be fed to the publisher,possibly affecting their decision about when and where to provideupdates, further information, new editions or even completely newpublications on topics that have proved to be of interest in existingbooks.

7.3. Printed Marks with Special Meaning or Containing Special Data

Many aspects of the system are enabled simply through the use of thetext already existing in a document. If the document is produced in theknowledge that it may be used in conjunction with the system, however,extra functionality can be added by printing extra information in theform of special marks, which may be used to identify the text or arequired action more closely, or otherwise enhance the document'sinteraction with the system. The simplest and most important example isan indication to the reader that the document is definitely accessiblethrough the system. A special icon might be used, for example, toindicate that this document has an online discussion forum associatedwith it.

Such symbols may be intended purely for the reader, or they may berecognized by the system when scanned and used to initiate some action.Sufficient data may be encoded in the symbol to identify more than justthe symbol: it may also store information, for example about thedocument, edition, and location of the symbol, which could be recognizedand read by the system.

7.4. Authorization Through Possession of the Paper Document

There are some situations where possession of or access to the printeddocument would entitle the user to certain privileges, for example, theaccess to an electronic copy of the document or to additional materials.With the described system, such privileges could be granted simply as aresult of the user capturing portions of text from the document, orscanning specially printed symbols. In cases where the system needed toensure that the user was in possession of the entire document, it mightprompt the user to scan particular items or phrases from particularpages, e.g. “the second line of page 46”.

7.5. Documents which Expire

If the printed document is a gateway to extra materials andfunctionality, access to such features can also be time-limited. Afterthe expiry date, a user may be required to pay a fee or obtain a newerversion of the document to access the features again. The paper documentwill, of course, still be usable, but will lose some of its enhancedelectronic functionality. This may be desirable, for example, becausethere is profit for the publisher in receiving fees for access toelectronic materials, or in requiring the user to purchase new editionsfrom time to time, or because there are disadvantages associated withoutdated versions of the printed document remaining in circulation.Coupons are an example of a type of commercial document that can have anexpiration date.

7.6. Popularity Analysis and Publishing Decisions

Section 10.5 discusses the use of the system's statistics to influencecompensation of authors and pricing of advertisements.

In some embodiments, the system deduces the popularity of a publicationfrom the activity in the electronic community associated with it as wellas from the use of the paper document. These factors may help publishersto make decisions about what they will publish in future. If a chapterin an existing book, for example, turns out to be exceedingly popular,it may be worth expanding into a separate publication.

8. Document Access Services

An important aspect of the described system is the ability to provide toa user who has access to a rendered copy of a document access to anelectronic version of that document. In some cases, a document is freelyavailable on a public network or a private network to which the user hasaccess. The system uses the captured text to identify, locate andretrieve the document, in some cases displaying it on the user's screenor depositing it in their email inbox.

In some cases, a document will be available in electronic form, but fora variety of reasons may not be accessible to the user. There may not besufficient connectivity to retrieve the document, the user may not beentitled to retrieve it, there may be a cost associated with gainingaccess to it, or the document may have been withdrawn and possiblyreplaced by a new version, to name just a few possibilities. The systemtypically provides feedback to the user about these situations.

As mentioned in Section 7.4, the degree or nature of the access grantedto a particular user may be different if it is known that the useralready has access to a printed copy of the document.

8.1. Authenticated Document Access

Access to the document may be restricted to specific users, or to thosemeeting particular criteria, or may only be available in certaincircumstances, for example when the user is connected to a securenetwork. Section 6 describes some of the ways in which the credentialsof a user and scanner may be established.

8.2. Document Purchase—Copyright-Owner Compensation

Documents that are not freely available to the general public may stillbe accessible on payment of a fee, often as compensation to thepublisher or copyright-holder. The system may implement paymentfacilities directly or may make use of other payment methods associatedwith the user, including those described in Section 6.2.

8.3. Document Escrow and Proactive Retrieval

Electronic documents are often transient; the digital source version ofa rendered document may be available now but inaccessible in future. Thesystem may retrieve and store the existing version on behalf of theuser, even if the user has not requested it, thus guaranteeing itsavailability should the user request it in future. This also makes itavailable for the system's use, for example for searching as part of theprocess of identifying future captures.

In the event that payment is required for access to the document, atrusted “document escrow” service can retrieve the document on behalf ofthe user, such as upon payment of a modest fee, with the assurance thatthe copyright holder will be fully compensated in future if the usershould ever request the document from the service.

Variations on this theme can be implemented if the document is notavailable in electronic form at the time of capture. The user canauthorize the service to submit a request for or make a payment for thedocument on his/her behalf if the electronic document should becomeavailable at a later date.

8.4. Association with Other Subscriptions and Accounts

Sometimes payment may be waived, reduced or satisfied based on theuser's existing association with another account or subscription.Subscribers to the printed version of a newspaper might automatically beentitled to retrieve the electronic version, for example.

In other cases, the association may not be quite so direct: a user maybe granted access based on an account established by their employer, orbased on their scanning of a printed copy owned by a friend who is asubscriber.

8.5. Replacing Photocopying with Scan-and-Print

The process of capturing text from a paper document, identifying anelectronic original, and printing that original, or some portion of thatoriginal associated with the capture, forms an alternative totraditional photocopying with many advantages:

-   -   the paper document need not be in the same location as the final        printout, and in any case need not be there at the same time    -   the wear and damage caused to documents by the photocopying        process, especially to old, fragile and valuable documents, can        be avoided    -   the quality of the copy is typically be much higher    -   records may be kept about which documents or portions of        documents are the most frequently copied    -   payment may be made to the copyright owner as part of the        process    -   unauthorized copying may be prohibited

8.6. Locating Valuable Originals from Photocopies

When documents are particularly valuable, as in the case of legalinstruments or documents that have historical or other particularsignificance, people may typically work from copies of those documents,often for many years, while the originals are kept in a safe location.

The described system could be coupled to a database which records thelocation of an original document, for example in an archiving warehouse,making it easy for somebody with access to a copy to locate the archivedoriginal paper document.

9. Text Recognition Technologies

Optical Character Recognition (OCR) technologies have traditionallyfocused on images that include a large amount of text, for example froma flat-bed scanner capturing a whole page. OCR technologies often needsubstantial training and correcting by the user to produce useful text.OCR technologies often require substantial processing power on themachine doing the OCR, and, while many systems use a dictionary, theyare generally expected to operate on an effectively infinite vocabulary.

All of the above traditional characteristics may be improved upon in thedescribed system.

While this section focuses on OCR, many of the issues discussed mapdirectly onto other recognition technologies, in particular speechrecognition. As mentioned in Section 3.1, the process of capturing frompaper may be achieved by a user reading the text aloud into a devicewhich captures audio. Those skilled in the art will appreciate thatprinciples discussed here with respect to images, fonts, and textfragments often also apply to audio samples, user speech models andphonemes.

9.1. Optimization for Appropriate Devices

A scanning device for use with the described system will often be small,portable, and low power. The scanning device may capture only a fewwords at a time, and in some implementations does not even capture awhole character at once, but rather a horizontal slice through the text,many such slices being stitched together to form a recognizable signalfrom which the text may be deduced. The scanning device may also havevery limited processing power or storage so, while in some embodimentsit may perform all of the OCR process itself, many embodiments willdepend on a connection to a more powerful device, possibly at a latertime, to convert the captured signals into text. Lastly, it may havevery limited facilities for user interaction, so may need to defer anyrequests for user input until later, or operate in a “best-guess” modeto a greater degree than is common now.

9.2. “Uncertain” OCR

The primary new characteristic of OCR within the described system is thefact that it will, in general, examine images of text which existselsewhere and which may be retrieved in digital form. An exacttranscription of the text is therefore not always required from the OCRengine. The OCR system may output a set or a matrix of possible matches,in some cases including probability weightings, which can still be usedto search for the digital original.

9.3. Iterative OCR—Guess, Disambiguate, Guess . . . .

If the device performing the recognition is able to contact the documentindex at the time of processing, then the OCR process can be informed bythe contents of the document corpus as it progresses, potentiallyoffering substantially greater recognition accuracy.

Such a connection will also allow the device to inform the user whensufficient text has been captured to identify the digital source.

9.4. Using Knowledge of Likely Rendering

When the system has knowledge of aspects of the likely printed renderingof a document—such as the font typeface used in printing, or the layoutof the page, or which sections are in italics—this too can help in therecognition process. (Section 4.1.1)

9.5. Font Caching—Determine Font on Host, Download to Client

As candidate source texts in the document corpus are identified, thefont, or a rendering of it, may be downloaded to the device to help withthe recognition.

9.6. Autocorrelation and Character Offsets

While component characters of a text fragment may be the most recognizedway to represent a fragment of text that may be used as a documentsignature, other representations of the text may work sufficiently wellthat the actual text of a text fragment need not be used when attemptingto locate the text fragment in a digital document and/or database, orwhen disambiguating the representation of a text fragment into areadable form. Other representations of text fragments may providebenefits that actual text representations lack. For example, opticalcharacter recognition of text fragments is often prone to errors, unlikeother representations of captured text fragments that may be used tosearch for and/or recreate a text fragment without resorting to opticalcharacter recognition for the entire fragment. Such methods may be moreappropriate for some devices used with the current system.

Those of ordinary skill in the art and others will appreciate that thereare many ways of describing the appearance of text fragments. Suchcharacterizations of text fragments may include, but are not limited to,word lengths, relative word lengths, character heights, characterwidths, character shapes, character frequencies, token frequencies, andthe like. In some embodiments, the offsets between matching text tokens(i.e., the number of intervening tokens plus one) are used tocharacterize fragments of text.

Conventional OCR uses knowledge about fonts, letter structure and shapeto attempt to determine characters in scanned text. Embodiments of thepresent invention are different; they employ a variety of methods thatuse the rendered text itself to assist in the recognition process. Theseembodiments use characters (or tokens) to “recognize each other.” Oneway to refer to such self-recognition is “template matching,” and issimilar to “convolution.” To perform such self-recognition, the systemslides a copy of the text horizontally over itself and notes matchingregions of the text images. Prior template matching and convolutiontechniques encompass a variety of related techniques. These techniquesto tokenize and/or recognize characters/tokens will be collectivelyreferred to herein as “autocorrelation,” as the text is used tocorrelate with its own component parts when matching characters/tokens.

When autocorrelating, complete connected regions that match are ofinterest. This occurs when characters (or groups of characters) overlayother instances of the same character (or group). Complete connectedregions that match automatically provide tokenizing of the text intocomponent tokens. As the two copies of the text are slid past eachother, the regions where perfect matching occurs (i.e., all pixels in avertical slice are matched) are noted. When a character/token matchesitself, the horizontal extent of this matching (e.g., the connectedmatching portion of the text) also matches.

Note that at this stage there is no need to determine the actualidentity of each token (i.e., the particular letter, digit or symbol, orgroup of these, that corresponds to the token image), only the offset tothe next occurrence of the same token in the scanned text. The offsetnumber is the distance (number of tokens) to the next occurrence of thesame token. If the token is unique within the text string, the offset iszero (0). The sequence of token offsets thus generated is a signaturethat can be used to identify the scanned text.

In some embodiments, the token offsets determined for a string ofscanned tokens are compared to an index that indexes a corpus ofelectronic documents based upon the token offsets of their contents(Section 4.1.2). In other embodiments, the token offsets determined fora string of scanned tokens are converted to text, and compared to a moreconventional index that indexes a corpus of electronic documents basedupon their contents

As has been noted earlier, a similar token-correlation process may beapplied to speech fragments when the capture process consists of audiosamples of spoken words.

9.7. Font/Character “Self-Recognition”

Conventional template-matching OCR compares scanned images to a libraryof character images. In essence, the alphabet is stored for each fontand newly scanned images are compared to the stored images to findmatching characters. The process generally has an initial delay untilthe correct font has been identified. After that, the OCR process isrelatively quick because most documents use the same font throughout.Subsequent images can therefore be converted to text by comparison withthe most recently identified font library.

The shapes of characters in most commonly used fonts are related. Forexample, in most fonts, the letter “c” and the letter “e” are visuallyrelated—as are “t” and “f”, etc. The OCR process is enhanced by use ofthis relationship to construct templates for letters that have not beenscanned yet. For example, where a reader scans a short string of textfrom a paper document in a previously unencountered font such that thesystem does not have a set of image templates with which to compare thescanned images the system can leverage the probable relationship betweencertain characters to construct the font template library even though ithas not yet encountered all of the letters in the alphabet. The systemcan then use the constructed font template library to recognizesubsequent scanned text and to further refine the constructed fontlibrary.

9.8. Send Anything Unrecognized (Including Graphics) to Server

When images cannot be machine-transcribed into a form suitable for usein a search process, the images themselves can be saved for later use bythe user, for possible manual transcription, or for processing at alater date when different resources may be available to the system.

10. P-Commerce

Many of the actions made possible by the system result in somecommercial transaction taking place. The phrase p-commerce is usedherein to describe commercial activities initiated from paper via thesystem.

10.1. Sales of Documents from their Physical Printed Copies.

When a user captures text from a document, the user may be offered thatdocument for purchase either in paper or electronic form. The user mayalso be offered related documents, such as those quoted or otherwisereferred to in the paper document, or those on a similar subject, orthose by the same author.

10.2. Sales of Anything Else Initiated or Aided by Paper

The capture of text may be linked to other commercial activities in avariety of ways. The captured text may be in a catalog that isexplicitly designed to sell items, in which case the text will beassociated fairly directly with the purchase of an item (Section 18.2).The text may also be part of an advertisement, in which case a sale ofthe item being advertised may ensue.

In other cases, the user captures other text from which their potentialinterest in a commercial transaction may be deduced. A reader of a novelset in a particular country, for example, might be interested in aholiday there. Someone reading a review of a new car might beconsidering purchasing it. The user may capture a particular fragment oftext knowing that some commercial opportunity will be presented to themas a result, or it may be a side-effect of their capture activities.

10.3. Capture of Labels, Icons, Serial Numbers, Barcodes on an ItemResulting in a Sale

Sometimes text or symbols are actually printed on an item or itspackaging. An example is the serial number or product id often found ona label on the back or underside of a piece of electronic equipment. Thesystem can offer the user a convenient way to purchase one or more ofthe same items by capturing that text. They may also be offered manuals,support or repair services.

10.4. Contextual Advertisements

In addition to the direct capture of text from an advertisement, thesystem allows for a new kind of advertising which is not necessarilyexplicitly in the rendered document, but is nonetheless based on whatpeople are reading.

10.4.1. Advertising Based on Scan Context and History

In a traditional paper publication, advertisements generally consume alarge amount of space relative to the text of a newspaper article, and alimited number of them can be placed around a particular article. In thedescribed system, advertising can be associated with individual words orphrases, and can selected according to the particular interest the userhas shown by capturing that text and possibly taking into account theirhistory of past scans.

With the described system, it is possible for a purchase to be tied to aparticular printed document and for an advertiser to get significantlymore feedback about the effectiveness of their advertising in particularprint publications.

10.4.2. Advertising Based on User Context and History

The system may gather a large amount of information about other aspectsof a user's context for its own use (Section 13); estimates of thegeographical location of the user are a good example. Such data can alsobe used to tailor the advertising presented to a user of the system.

10.5. Models of Compensation

The system enables some new models of compensation for advertisers andmarketers. The publisher of a printed document containing advertisementsmay receive some income from a purchase that originated from theirdocument. This may be true whether or not the advertisement existed inthe original printed form; it may have been added electronically eitherby the publisher, the advertiser or some third party, and the sources ofsuch advertising may have been subscribed to by the user.

10.5.1. Popularity-Based Compensation

Analysis of the statistics generated by the system can reveal thepopularity of certain parts of a publication (Section 14.2). In anewspaper, for example, it might reveal the amount of time readers spendlooking at a particular page or article, or the popularity of aparticular columnist. In some circumstances, it may be appropriate foran author or publisher to receive compensation based on the activitiesof the readers rather than on more traditional metrics such as wordswritten or number of copies distributed. An author whose work becomes afrequently read authority on a subject might be considered differentlyin future contracts from one whose books have sold the same number ofcopies but are rarely opened. (See also Section 7.6)

10.5.2. Popularity-Based Advertising

Decisions about advertising in a document may also be based onstatistics about the readership. The advertising space around the mostpopular columnists may be sold at a premium rate. Advertisers might evenbe charged or compensated some time after the document is publishedbased on knowledge about how it was received.

10.6. Marketing Based on Life Library

The “Life Library” or scan history described in Sections 6.1 and 16.1can be an extremely valuable source of information about the interestsand habits of a user. Subject to the appropriate consent and privacyissues, such data can inform offers of goods or services to the user.Even in an anonymous form, the statistics gathered can be exceedinglyuseful.

10.7. Sale/Information at Later Date (when Available)

Advertising and other opportunities for commercial transactions may notbe presented to the user immediately at the time of text capture. Forexample, the opportunity to purchase a sequel to a novel may not beavailable at the time the user is reading the novel, but the system maypresent them with that opportunity when the sequel is published.

A user may capture data that relates to a purchase or other commercialtransaction, but may choose not to initiate and/or complete thetransaction at the time the capture is made. In some embodiments, datarelated to captures is stored in a user's Life Library, and these LifeLibrary entries can remain “active” (i.e., capable of subsequentinteractions similar to those available at the time the capture wasmade). Thus a user may review a capture at some later time, andoptionally complete a transaction based on that capture. Because thesystem can keep track of when and where the original capture occurred,all parties involved in the transaction can be properly compensated. Forexample, the author who wrote the story—and the publisher who publishedthe story—that appeared next to the advertisement from which the usercaptured data can be compensated when, six months later, the user visitstheir Life Library, selects that particular capture from the history,and chooses “Purchase this item at Amazon” from the pop-up menu (whichcan be similar or identical to the menu optionally presented at the timeof the capture).

11. Operating System and Application Integration

Modern Operating Systems (OSs) and other software packages have manycharacteristics that can be advantageously exploited for use with thedescribed system, and may also be modified in various ways to provide aneven better platform for its use.

11.1. Incorporation of Scan and Print-Related Information in Metadataand Indexing

New and upcoming file systems and their associated databases often havethe ability to store a variety of metadata associated with each file.Traditionally, this metadata has included such things as the ID of theuser who created the file, the dates of creation, last modification, andlast use. Newer file systems allow such extra information as keywords,image characteristics, document sources and user comments to be stored,and in some systems this metadata can be arbitrarily extended. Filesystems can therefore be used to store information that would be usefulin implementing the current system. For example, the date when a givendocument was last printed can be stored by the file system, as candetails about which text from it has been captured from paper using thedescribed system, and when and by whom.

Operating systems are also starting to incorporate search enginefacilities that allow users to find local files more easily. Thesefacilities can be advantageously used by the system. It means that manyof the search-related concepts discussed in Sections 3 and 4 apply notjust to today's Internet-based and similar search engines, but also toevery personal computer.

In some cases specific software applications will also include supportfor the system above and beyond the facilities provided by the OS.

11.2. OS Support for Capture Devices

As the use of capture devices such as pen scanners becomes increasinglycommon, it will become desirable to build support for them into theoperating system, in much the same way as support is provided for miceand printers, since the applicability of capture devices extends beyonda single software application. The same will be true for other aspectsof the system's operation. Some examples are discussed below. In someembodiments, the entire described system, or the core of it, is providedby the OS. In some embodiments, support for the system is provided byApplication Programming Interfaces (APIs) that can be used by othersoftware packages, including those directly implementing aspects of thesystem.

11.2.1. Support for OCR and Other Recognition Technologies

Most of the methods of capturing text from a rendered document requiresome recognition software to interpret the source data, typically ascanned image or some spoken words, as text suitable for use in thesystem. Some OSs include support for speech or handwriting recognition,though it is less common for OSs to include support for OCR, since inthe past the use of OCR has typically been limited to a small range ofapplications.

As recognition components become part of the OS, they can take betteradvantage of other facilities provided by the OS. Many systems includespelling dictionaries, grammar analysis tools, internationalization andlocalization facilities, for example, all of which can be advantageouslyemployed by the described system for its recognition process, especiallysince they may have been customized for the particular user to includewords and phrases that he/she would commonly encounter.

If the operating system includes full-text indexing facilities, thenthese can also be used to inform the recognition process, as describedin Section 9.3.

11.2.2. Action to be Taken on Scans

If an optical scan or other capture occurs and is presented to the OS,it may have a default action to be taken under those circumstances inthe event that no other subsystem claims ownership of the capture. Anexample of a default action is presenting the user with a choice ofalternatives, or submitting the captured text to the OS's built-insearch facilities.

11.2.3. OS has Default Action for Particular Documents or Document Types

If the digital source of the rendered document is found, the OS may havea standard action that it will take when that particular document, or adocument of that class, is scanned. Applications and other subsystemsmay register with the OS as potential handlers of particular types ofcapture, in a similar manner to the announcement by applications oftheir ability to handle certain file types.

Markup data associated with a rendered document, or with a capture froma document, can include instructions to the operating system to launchspecific applications, pass applications arguments, parameters, or data,etc.

11.2.4. Interpretation of Gestures and Mapping into Standard Actions

In Section 12.1.3 the use of “gestures” is discussed, particularly inthe case of optical scanning, where particular movements made with ahandheld scanner might represent standard actions such as marking thestart and end of a region of text.

This is analogous to actions such as pressing the shift key on akeyboard while using the cursor keys to select a region of text, orusing the wheel on a mouse to scroll a document. Such actions by theuser are sufficiently standard that they are interpreted in asystem-wide way by the OS, thus ensuring consistent behavior. The sameis desirable for scanner gestures and other scanner-related actions.

11.2.5. Set Response to Standard (and Non-Standard) Iconic/Text PrintedMenu Items

In a similar way, certain items of text or other symbols may, whenscanned, cause standard actions to occur, and the OS may provide aselection of these. An example might be that scanning the text “[print]”in any document would cause the OS to retrieve and print a copy of thatdocument. The OS may also provide a way to register such actions andassociate them with particular scans.

11.3. Support in System GUI Components for Typical Scan-InitiatedActivities

Most software applications are based substantially on standard GraphicalUser Interface components provided by the OS.

Use of these components by developers helps to ensure consistentbehavior across multiple packages, for example that pressing theleft-cursor key in any text-editing context should move the cursor tothe left, without every programmer having to implement the samefunctionality independently.

A similar consistency in these components is desirable when theactivities are initiated by text-capture or other aspects of thedescribed system. Some examples are given below.

11.3.1. Interface to Find Particular Text Content

A typical use of the system may be for the user to scan an area of apaper document, and for the system to open the electronic counterpart ina software package that is able to display or edit it, and cause thatpackage to scroll to and highlight the scanned text (Section 12.2.1).The first part of this process, finding and opening the electronicdocument, is typically provided by the OS and is standard acrosssoftware packages. The second part, however—locating a particular pieceof text within a document and causing the package to scroll to it andhighlight it—is not yet standardized and is often implementeddifferently by each package. The availability of a standard API for thisfunctionality could greatly enhance the operation of this aspect of thesystem.

11.3.2. Text Interactions

Once a piece of text has been located within a document, the system maywish to perform a variety of operations upon that text. As an example,the system may request the surrounding text, so that the user's captureof a few words could result in the system accessing the entire sentenceor paragraph containing them. Again, this functionality can be usefullyprovided by the OS rather than being implemented in every piece ofsoftware that handles text.

11.3.3. Contextual (Popup) Menus

Some of the operations that are enabled by the system will require userfeedback, and this may be optimally requested within the context of theapplication handling the data. In some embodiments, the system uses theapplication pop-up menus traditionally associated with clicking theright mouse button on some text. The system inserts extra options intosuch menus, and causes them to be displayed as a result of activitiessuch as scanning a paper document.

11.4. Web/Network Interfaces

In today's increasingly networked world, much of the functionalityavailable on individual machines can also be accessed over a network,and the functionality associated with the described system is noexception. As an example, in an office environment, many paper documentsreceived by a user may have been printed by other users' machines on thesame corporate network. The system on one computer, in response to acapture, may be able to query those other machines for documents whichmay correspond to that capture, subject to the appropriate permissioncontrols.

11.5. Printing of Document Causes Saving

An important factor in the integration of paper and digital documents ismaintaining as much information as possible about the transitionsbetween the two. In some embodiments, the OS keeps a simple record ofwhen any document was printed and by whom. In some embodiments, the OStakes one or more further actions that would make it better suited foruse with the system. Examples include:

-   -   Saving the digital rendered version of every document printed        along with information about the source from which it was        printed    -   Saving a subset of useful information about the printed        version—for example, the fonts used and where the line breaks        occur—which might aid future scan interpretation    -   Saving the version of the source document associated with any        printed copy    -   Indexing the document automatically at the time of printing and        storing the results for future searching

11.6. My (Printed/Scanned) Documents

An OS often maintains certain categories of folders or files that haveparticular significance. A user's documents may, by convention ordesign, be found in a “My Documents” folder, for example. Standardfile-opening dialogs may automatically include a list of recently openeddocuments.

On an OS optimized for use with the described system, such categoriesmay be enhanced or augmented in ways that take into account a user'sinteraction with paper versions of the stored files. Categories such as“My Printed Documents” or “My Recently-Read Documents” might usefully beidentified and incorporated in its operations.

11.7. OS-Level Markup Hierarchies

Since important aspects of the system are typically provided using the“markup” concepts discussed in Section 5, it would clearly beadvantageous to have support for such markup provided by the OS in a waythat was accessible to multiple applications as well as to the OSitself. In addition, layers of markup may be provided by the OS, basedon its own knowledge of documents under its control and the facilitiesit is able to provide.

11.8. Use of OS DRM Facilities

An increasing number of operating systems support some form of “DigitalRights Management”: the ability to control the use of particular dataaccording to the rights granted to a particular user, software entity ormachine. It may inhibit unauthorized copying or distribution of aparticular document, for example.

12. User Interface

The user interface of the system may be entirely on a PC, if the capturedevice is relatively dumb and is connected to it by a cable, or entirelyon the device, if it is sophisticated and with significant processingpower of its own. In some cases, some functionality resides in eachcomponent. Part, or indeed all, of the system's functionality may alsobe implemented on other devices such as mobile phones or PDAs.

The descriptions in the following sections are therefore indications ofwhat may be desirable in certain implementations, but they are notnecessarily appropriate for all and may be modified in several ways.

12.1. On the Capture Device

With all capture devices, but particularly in the case of an opticalscanner, the user's attention will generally be on the device and thepaper at the time of scanning. It is very desirable, then, that anyinput and feedback needed as part of the process of scanning do notrequire the user's attention to be elsewhere, for example on the screenof a computer, more than is necessary.

12.1.1. Feedback on Scanner

A handheld scanner may have a variety of ways of providing feedback tothe user about particular conditions. The most obvious types are directvisual, where the scanner incorporates indicator lights or even a fulldisplay, and auditory, where the scanner can make beeps, clicks or othersounds. Important alternatives include tactile feedback, where thescanner can vibrate, buzz, or otherwise stimulate the user's sense oftouch, and projected feedback, where it indicates a status by projectingonto the paper anything from a colored spot of light to a sophisticateddisplay.

Important immediate feedback that may be provided on the deviceincludes:

-   -   feedback on the scanning process—user scanning too fast, at too        great an angle, or drifting too high or low on a particular line    -   sufficient content—enough has been scanned to be pretty certain        of finding a match if one exists—important for disconnected        operation    -   context known—a source of the text has been located    -   unique context known—one unique source of the text has been        located    -   availability of content—indication of whether the content is        freely available to the user, or at a cost

Many of the user interactions normally associated with the later stagesof the system may also take place on the capture device if it hassufficient abilities, for example, to display part or all of a document.

12.1.2. Controls on Scanner

The device may provide a variety of ways for the user to provide inputin addition to basic text capture. Even when the device is in closeassociation with a host machine that has input options such as keyboardsand mice, it can be disruptive for the user to switch back and forthbetween manipulating the scanner and using a mouse, for example.

The handheld scanner may have buttons, scroll/jog-wheels,touch-sensitive surfaces, and/or accelerometers for detecting themovement of the device. Some of these allow a richer set of interactionswhile still holding the scanner.

For example, in response to scanning some text, the system presents theuser with a set of several possible matching documents. The user uses ascroll-wheel on the side of the scanner is to select one from the list,and clicks a button to confirm the selection.

12.1.3. Gestures

The primary reason for moving a scanner across the paper is to capturetext, but some movements may be detected by the device and used toindicate other user intentions. Such movements are referred to herein as“gestures”.

As an example, the user can indicate a large region of text by scanningthe first few words in conventional left-to-right order, and the lastfew in reverse order, i.e. right to left. The user can also indicate thevertical extent of the text of interest by moving the scanner down thepage over several lines. A backwards scan might indicate cancellation ofthe previous scan operation.

12.1.4. Online/Offline Behavior

Many aspects of the system may depend on network connectivity, eitherbetween components of the system such as a scanner and a host laptop, orwith the outside world in the form of a connection to corporatedatabases and Internet search. This connectivity may not be present allthe time, however, and so there will be occasions when part or all ofthe system may be considered to be “offline”. It is desirable to allowthe system to continue to function usefully in those circumstances.

The device may be used to capture text when it is out of contact withother parts of the system. A very simple device may simply be able tostore the image or audio data associated with the capture, ideally witha timestamp indicating when it was captured. The various captures may beuploaded to the rest of the system when the device is next in contactwith it, and handled then. The device may also upload other dataassociated with the captures, for example voice annotations associatedwith optical scans, or location information.

More sophisticated devices may be able to perform some or all of thesystem operations themselves despite being disconnected. Varioustechniques for improving their ability to do so are discussed in Section15.3. Often it will be the case that some, but not all, of the desiredactions can be performed while offline. For example, the text may berecognized, but identification of the source may depend on a connectionto an Internet-based search engine. In some embodiments, the devicetherefore stores sufficient information about how far each operation hasprogressed for the rest of the system to proceed efficiently whenconnectivity is restored.

The operation of the system will, in general, benefit from immediatelyavailable connectivity, but there are some situations in whichperforming several captures and then processing them as a batch can haveadvantages. For example, as discussed in Section 13 below, theidentification of the source of a particular capture may be greatlyenhanced by examining other captures made by the user at approximatelythe same time. In a fully connected system where live feedback is beingprovided to the user, the system is only able to use past captures whenprocessing the current one. If the capture is one of a batch stored bythe device when offline, however, the system will be able to take intoaccount any data available from later captures as well as earlier oneswhen doing its analysis.

12.2. On a Host Device

A scanner will often communicate with some other device, such as a PC,PDA, phone or digital camera to perform many of the functions of thesystem, including more detailed interactions with the user.

12.2.1. Activities Performed in Response to a Capture

When the host device receives a capture, it may initiate a variety ofactivities. An incomplete list of possible activities performed by thesystem after locating and electronic counterpart document associatedwith the capture and a location within that document follows.

-   -   The details of the capture may be stored in the user's history.        (Section 6.1)    -   The document may be retrieved from local storage or a remote        location. (Section 8)    -   The operating system's metadata and other records associated        with the document may be updated. (Section 11.1)    -   Markup associated with the document may be examined to determine        the next relevant operations. (Section 5)    -   A software application may be started to edit, view or otherwise        operate on the document. The choice of application may depend on        the source document, or on the contents of the scan, or on some        other aspect of the capture. (Section 11.2.2, 11.2.3)    -   The application may scroll to, highlight, move the insertion        point to, or otherwise indicate the location of the capture.        (Section 11.3)    -   The precise bounds of the captured text may be modified, for        example to select whole words, sentences or paragraphs around        the captured text. (Section 11.3.2)    -   The user may be given the option to copy the capture text to the        clipboard or perform other standard operating system or        application-specific operations upon it.    -   Annotations may be associated with the document or the captured        text. These may come from immediate user input, or may have been        captured earlier, for example in the case of voice annotations        associated with an optical scan. (Section 19.4)    -   Markup may be examined to determine a set of further possible        operations for the user to select.

12.2.2. Contextual Popup Menus

Sometimes the appropriate action to be taken by the system will beobvious, but sometimes it will require a choice to be made by the user.One good way to do this is through the use of “popup menus” or, in caseswhere the content is also being displayed on a screen, with so-called“contextual menus” that appear close to the content. (See Section11.3.3). In some embodiments, the scanner device projects a popup menuonto the paper document. A user may select from such menus usingtraditional methods such as a keyboard and mouse, or by using controlson the capture device (Section 12.1.2), gestures (Section 12.1.3), or byinteracting with the computer display using the scanner (Section12.2.4). In some embodiments, the popup menus which can appear as aresult of a capture include default items representing actions whichoccur if the user does not respond—for example, if the user ignores themenu and makes another capture.

12.2.3. Feedback on Disambiguation

When a user starts capturing text, there will initially be severaldocuments or other text locations that it could match. As more text iscaptured, and other factors are taken into account (Section 13), thenumber of candidate locations will decrease until the actual location isidentified, or further disambiguation is not possible without userinput. In some embodiments, the system provides a real-time display ofthe documents or the locations found, for example in list,thumbnail-image or text-segment form, and for the number of elements inthat display to reduce in number as capture continues. In someembodiments, the system displays thumbnails of all candidate documents,where the size or position of the thumbnail is dependent on theprobability of it being the correct match.

When a capture is unambiguously identified, this fact may be emphasizedto the user, for example using audio feedback.

Sometimes the text captured will occur in many documents and will berecognized to be a quotation. The system may indicate this on thescreen, for example by grouping documents containing a quoted referencearound the original source document.

12.2.4. Scanning from Screen

Some optical scanners may be able to capture text displayed on a screenas well as on paper. Accordingly, the term rendered document is usedherein to indicate that printing onto paper is not the only form ofrendering, and that the capture of text or symbols for use by the systemmay be equally valuable when that text is displayed on an electronicdisplay.

The user of the described system may be required to interact with acomputer screen for a variety of other reasons, such as to select from alist of options. It can be inconvenient for the user to put down thescanner and start using the mouse or keyboard. Other sections havedescribed physical controls on the scanner (Section 12.1.2) or gestures(Section 12.1.3) as methods of input which do not require this change oftool, but using the scanner on the screen itself to scan some text orsymbol is an important alternative provided by the system.

In some embodiments, the optics of the scanner allow it to be used in asimilar manner to a light-pen, directly sensing its position on thescreen without the need for actual scanning of text, possibly with theaid of special hardware or software on the computer.

13. Context Interpretation

An important aspect of the described system is the use of other factors,beyond the simple capture of a string of text, to help identify thedocument in use. A capture of a modest amount of text may often identifythe document uniquely, but in many situations it will identify a fewcandidate documents. One solution is to prompt the user to confirm thedocument being scanned, but a preferable alternative is to make use ofother factors to narrow down the possibilities automatically. Suchsupplemental information can dramatically reduce the amount of text thatneeds to be captured and/or increase the reliability and speed withwhich the location in the electronic counterpart can be identified. Thisextra material is referred to as “context”, and it was discussed brieflyin Section 4.2.2. We now consider it in more depth.

13.1. System and Capture Context

Perhaps the most important example of such information is the user'scapture history.

It is highly probable that any given capture comes from the samedocument as the previous one, or from an associated document, especiallyif the previous capture took place in the last few minutes (Section6.1.2). Conversely, if the system detects that the font has changedbetween two scans, it is more likely that they are from differentdocuments.

Also useful are the user's longer-term capture history and readinghabits. These can also be used to develop a model of the user'sinterests and associations.

13.2. User's Real-World Context

Another example of useful context is the user's geographical location. Auser in Paris is much more likely to be reading Le Monde than theSeattle Times, for example. The timing, size and geographicaldistribution of printed versions of the documents can therefore beimportant, and can to some degree be deduced from the operation of thesystem.

The time of day may also be relevant, for example in the case of a userwho always reads one type of publication on the way to work, and adifferent one at lunchtime or on the train going home.

13.3. Related Digital Context

The user's recent use of electronic documents, including those searchedfor or retrieved by more conventional means, can also be a helpfulindicator.

In some cases, such as on a corporate network, other factors may beusefully considered:

-   -   Which documents have been printed recently?    -   Which documents have been modified recently on the corporate        file server?    -   Which documents have been emailed recently?

All of these examples might suggest that a user was more likely to bereading a paper version of those documents. In contrast, if therepository in which a document resides can affirm that the document hasnever been printed or sent anywhere where it might have been printed,then it can be safely eliminated in any searches originating from paper.

13.4. Other Statistics—the Global Context

Section 14 covers the analysis of the data stream resulting frompaper-based searches, but it should be noted here that statistics aboutthe popularity of documents with other readers, about the timing of thatpopularity, and about the parts of documents most frequently scanned areall examples of further factors which can be beneficial in the searchprocess. The system brings the possibility of Google-type page-rankingto the world of paper.

See also Section 4.2.2 for some other implications of the use of contextfor search engines.

14. Data-Stream Analysis

The use of the system generates an exceedingly valuable data-stream as aside effect. This stream is a record of what users are reading and when,and is in many cases a record of what they find particularly valuable inthe things they read. Such data has never really been available beforefor paper documents.

Some ways in which this data can be useful for the system, and for theuser of the system, are described in Section 6.1. This sectionconcentrates on its use for others. There are, of course, substantialprivacy issues to be considered with any distribution of data about whatpeople are reading, but such issues as preserving the anonymity of dataare well known to those of skill in the art.

14.1. Document Tracking

When the system knows which documents any given user is reading, it canalso deduce who is reading any given document. This allows the trackingof a document through an organization, to allow analysis, for example,of who is reading it and when, how widely it was distributed, how longthat distribution took, and who has seen current versions while othersare still working from out-of-date copies.

For published documents that have a wider distribution, the tracking ofindividual copies is more difficult, but the analysis of thedistribution of readership is still possible.

14.2. Read Ranking—Popularity of Documents and Sub-Regions

In situations where users are capturing text or other data that is ofparticular interest to them, the system can deduce the popularity ofcertain documents and of particular sub-regions of those documents. Thisforms a valuable input to the system itself (Section 4.2.2) and animportant source of information for authors, publishers and advertisers(Section 7.6, Section 10.5). This data is also useful when integrated insearch engines and search indices—for example, to assist in rankingsearch results for queries coming from rendered documents, and/or toassist in ranking conventional queries typed into a web browser.

14.3. Analysis of Users—Building Profiles

Knowledge of what a user is reading enables the system to create a quitedetailed model of the user's interests and activities. This can beuseful on an abstract statistical basis—“35% of users who buy thisnewspaper also read the latest book by that author”—but it can alsoallow other interactions with the individual user, as discussed below.

14.3.1. Social Networking

One example is connecting one user with others who have relatedinterests. These may be people already known to the user. The system mayask a university professor, “Did you know that your colleague at XYZUniversity has also just read this paper?” The system may ask a user,“Do you want to be linked up with other people in your neighborhood whoare also how reading Jane Eyre?” Such links may be the basis for theautomatic formation of book clubs and similar social structures, eitherin the physical world or online.

14.3.2. Marketing

Section 10.6 has already mentioned the idea of offering products andservices to an individual user based on their interactions with thesystem. Current online booksellers, for example, often makerecommendations to a user based on their previous interactions with thebookseller. Such recommendations become much more useful when they arebased on interactions with the actual books.

14.4. Marketing Based on Other Aspects of the Data-Stream

We have discussed some of the ways in which the system may influencethose publishing documents, those advertising through them, and othersales initiated from paper (Section 10). Some commercial activities mayhave no direct interaction with the paper documents at all and yet maybe influenced by them. For example, the knowledge that people in onecommunity spend more time reading the sports section of the newspaperthan they do the financial section might be of interest to somebodysetting up a health club.

14.5. Types of Data that May be Captured

In addition to the statistics discussed, such as who is reading whichbits of which documents, and when and where, it can be of interest toexamine the actual contents of the text captured, regardless of whetheror not the document has been located.

In many situations, the user will also not just be capturing some text,but will be causing some action to occur as a result. It might beemailing a reference to the document to an acquaintance, for example.Even in the absence of information about the identity of the user or therecipient of the email, the knowledge that somebody considered thedocument worth emailing is very useful.

In addition to the various methods discussed for deducing the value of aparticular document or piece of text, in some circumstances the userwill explicitly indicate the value by assigning it a rating.

Lastly, when a particular set of users are known to form a group, forexample when they are known to be employees of a particular company, theaggregated statistics of that group can be used to deduce the importanceof a particular document to that group.

15. Device Features and Functions

A capture device for use with the system needs little more than a way ofcapturing text from a rendered version of the document. As describedearlier (Section 1.2), this capture may be achieved through a variety ofmethods including taking a photograph of part of the document or typingsome words into a mobile phone keypad. This capture may be achievedusing a small hand-held optical scanner capable of recording a line ortwo of text at a time, or an audio capture device such as avoice-recorder into which the user is reading text from the document.The device used may be a combination of these—an optical scanner whichcould also record voice annotations, for example—and the capturingfunctionality may be built into some other device such as a mobilephone, PDA, digital camera or portable music player.

15.1. Input and Output

Many of the possibly beneficial additional input and output facilitiesfor such a device have been described in Section 12.1. They includebuttons, scroll-wheels and touch-pads for input, and displays, indicatorlights, audio and tactile transducers for output. Sometimes the devicewill incorporate many of these, sometimes very few. Sometimes thecapture device will be able to communicate with another device thatalready has them (Section 15.6), for example using a wireless link, andsometimes the capture functionality will be incorporated into such otherdevice (Section 15.7).

15.2. Connectivity

In some embodiments, the device implements the majority of the systemitself. In some embodiments, however, it often communicates with a PC orother computing device and with the wider world using communicationsfacilities.

Often these communications facilities are in the form of ageneral-purpose data network such as Ethernet, 802.11 or UWB or astandard peripheral-connecting network such as USB, IEEE-1394(Firewire), Bluetooth™ or infra-red. When a wired connection such asFirewire or USB is used, the device may receive electrical power thoughthe same connection. In some circumstances, the capture device mayappear to a connected machine to be a conventional peripheral such as aUSB storage device.

Lastly, the device may in some circumstances “dock” with another device,either to be used in conjunction with that device or for convenientstorage.

15.3. Caching and Other Online/Offline Functionality

Sections 3.5 and 12.1.4 have raised the topic of disconnected operation.When a capture device has a limited subset of the total system'sfunctionality, and is not in communication with the other parts of thesystem, the device can still be useful, though the functionalityavailable will sometimes be reduced. At the simplest level, the devicecan record the raw image or audio data being captured and this can beprocessed later. For the user's benefit, however, it can be important togive feedback where possible about whether the data captured is likelyto be sufficient for the task in hand, whether it can be recognized oris likely to be recognizable, and whether the source of the data can beidentified or is likely to be identifiable later. The user will thenknow whether their capturing activity is worthwhile. Even when all ofthe above are unknown, the raw data can still be stored so that, at thevery least, the user can refer to them later. The user may be presentedwith the image of a scan, for example, when the scan cannot berecognized by the OCR process.

To illustrate some of the range of options available, both a ratherminimal optical scanning device and then a much more full-featured oneare described below. Many devices occupy a middle ground between thetwo.

15.3.1. The SimpleScanner—a Low-End Offline Example

The SimpleScanner has a scanning head able to read pixels from the pageas it is moved along the length of a line of text. It can detect itsmovement along the page and record the pixels with some informationabout the movement. It also has a clock, which allows each scan to betime-stamped. The clock is synchronized with a host device when theSimpleScanner has connectivity. The clock may not represent the actualtime of day, but relative times may be determined from it so that thehost can deduce the actual time of a scan, or at worst the elapsed timebetween scans.

The SimpleScanner does not have sufficient processing power to performany OCR itself, but it does have some basic knowledge about typicalword-lengths, word-spacings, and their relationship to font size. It hassome basic indicator lights which tell the user whether the scan islikely to be readable, whether the head is being moved too fast, tooslowly or too inaccurately across the paper, and when it determines thatsufficient words of a given size are likely to have been scanned for thedocument to be identified.

The SimpleScanner has a USB connector and can be plugged into the USBport on a computer, where it will be recharged. To the computer itappears to be a USB storage device on which time-stamped data files havebeen recorded, and the rest of the system software takes over from thispoint.

15.3.2. The SuperScanner—a High-End Offline Example

The SuperScanner also depends on connectivity for its full operation,but it has a significant amount of on-board storage and processing whichcan help it make better judgments about the data captured while offline.

As it moves along the line of text, the captured pixels are stitchedtogether and passed to an OCR engine that attempts to recognize thetext. A number of fonts, including those from the user's most-readpublications, have been downloaded to it to help perform this task, ashas a dictionary that is synchronized with the user's spelling-checkerdictionary on their PC and so contains many of the words they frequentlyencounter. Also stored on the scanner is a list of words and phraseswith the typical frequency of their use—this may be combined with thedictionary. The scanner can use the frequency statistics both to helpwith the recognition process and also to inform its judgment about whena sufficient quantity of text has been captured; more frequently usedphrases are less likely to be useful as the basis for a search query.

In addition, the full index for the articles in the recent issues of thenewspapers and periodicals most commonly read by the user are stored onthe device, as are the indices for the books the user has recentlypurchased from an online bookseller, or from which the user has scannedanything within the last few months. Lastly, the titles of severalthousand of the most popular publications which have data available forthe system are stored so that, in the absence of other information theuser can scan the title and have a good idea as to whether or notcaptures from a particular work are likely to be retrievable inelectronic form later.

During the scanning process, the system informs user that the captureddata has been of sufficient quality and of a sufficient nature to makeit probable that the electronic copy can be retrieved when connectivityis restored. Often the system indicates to the user that the scan isknown to have been successful and that the context has peen recognizedin one of the on-board indices, or that the publication concerned isknown to be making its data available to the system, so the laterretrieval ought to be successful.

The SuperScanner docks in a cradle connected to a PC's Firewire or USBport, at which point, in addition to the upload of captured data, itsvarious onboard indices and other databases are updated based on recentuser activity and new publications. It also has the facility to connectto wireless public networks or to communicate via Bluetooth to a mobilephone and thence with the public network when such facilities areavailable.

15.4. Features for Optical Scanning

We now consider some of the features that may be particularly desirablein an optical scanner device.

15.4.1. Flexible Positioning and Convenient Optics

One of the reasons for the continuing popularity of paper is the ease ofits use in a wide variety of situations where a computer, for example,would be impractical or inconvenient. A device intended to capture asubstantial part of a user's interaction with paper should therefore besimilarly convenient in use. This has not been the case for scanners inthe past; even the smallest hand-held devices have been somewhatunwieldy. Those designed to be in contact with the page have to be heldat a precise angle to the paper and moved very carefully along thelength of the text to be scanned. This is acceptable when scanning abusiness report on an office desk, but may be impractical when scanninga phrase from a novel while waiting for a train. Scanners based oncamera-type optics that operate at a distance from the paper maysimilarly be useful in some circumstances.

Some embodiments of the system use a scanner that scans in contact withthe paper, and which, instead of lenses, uses an image conduit a bundleof optical fibers to transmit the image from the page to the opticalsensor device. Such a device can be shaped to allow it to be held in anatural position; for example, in some embodiments, the part in contactwith the page is wedge-shaped, allowing the user's hand to move morenaturally over the page in a movement similar to the use of ahighlighter pen. The conduit is either in direct contact with the paperor in close proximity to it, and may have a replaceable transparent tipthat can protect the image conduit from possible damage. As has beenmentioned in Section 12.2.4, the scanner may be used to scan from ascreen as well as from paper, and the material of the tip can be chosento reduce the likelihood of damage to such displays.

Lastly, some embodiments of the device will provide feedback to the userduring the scanning process which will indicate through the use oflight, sound or tactile feedback when the user is scanning too fast, tooslow, too unevenly or is drifting too high or low on the scanned line.

15.5. Security, Identity, Authentication, Personalization and Billing

As described in Section 6, the capture device may form an important partof identification and authorization for secure transactions, purchases,and a variety of other operations. It may therefore incorporate, inaddition to the circuitry and software required for such a role, varioushardware features that can make it more secure, such as a smartcardreader, RFID, or a keypad on which to type a PIN.

It may also include various biometric sensors to help identify the user.In the case of an optical scanner, for example, the scanning head mayalso be able to read a fingerprint. For a voice recorder, the voicepattern of the user may be used.

15.6. Device Associations

In some embodiments, the device is able to form an association withother nearby devices to increase either its own or their functionality.In some embodiments, for example, it uses the display of a nearby PC orphone to give more detailed feedback about its operation, or uses theirnetwork connectivity. The device may, on the other hand, operate in itsrole as a security and identification device to authenticate operationsperformed by the other device. Or it may simply form an association inorder to function as a peripheral to that device.

An interesting aspect of such associations is that they may be initiatedand authenticated using the capture facilities of the device. Forexample, a user wishing to identify themselves securely to a publiccomputer terminal may use the scanning facilities of the device to scana code or symbol displayed on a particular area of the terminal's screenand so effect a key transfer. An analogous process may be performedusing audio signals picked up by a voice-recording device.

15.7. Integration with Other Devices

In some embodiments, the functionality of the capture device isintegrated into some other device that is already in use. The integrateddevices may be able to share a power supply, data capture and storagecapabilities, and network interfaces. Such integration may be donesimply for convenience, to reduce cost, or to enable functionality thatwould not otherwise be available.

Some examples of devices into which the capture functionality can beintegrated include:

-   -   an existing peripheral such as a mouse, a stylus, a USB “webcam”        camera, a Bluetooth™ headset or a remote control    -   another processing/storage device, such as a PDA, an MP3 player,        a voice recorder, a digital camera or a mobile phone    -   other often-carried items, just for convenience—a watch, a piece        of jewelry, a pen, a car key fob

15.7.1. Mobile Phone Integration

As an example of the benefits of integration, we consider the use of amodified mobile phone as the capture device.

In some embodiments, the phone hardware is not modified to support thesystem, such as where the text capture can be adequately done throughvoice recognition, where they can either be processed by the phoneitself, or handled by a system at the other end of a telephone call, orstored in the phone's memory for future processing. Many modern phoneshave the ability to download software that could implement some parts ofthe system. Such voice capture is likely to be suboptimal in manysituations, however, for example when there is substantial backgroundnoise, and accurate voice recognition is a difficult task at the best oftimes. The audio facilities may best be used to capture voiceannotations.

In some embodiments, the camera built into many mobile phones is used tocapture an image of the text. The phone display, which would normallyact as a viewfinder for the camera, may overlay on the live camera imageinformation about the quality of the image and its suitability for OCR,which segments of text are being captured, and even a transcription ofthe text if the OCR can be performed on the phone.

In some embodiments, the phone is modified to add dedicated capturefacilities, or to provide such functionality in a clip-on adaptor or aseparate Bluetooth-connected peripheral in communication with the phone.Whatever the nature of the capture mechanism, the integration with amodern cellphone has many other advantages. The phone has connectivitywith the wider world, which means that queries can be submitted toremote search engines or other parts of the system, and copies ofdocuments may be retrieved for immediate storage or viewing. A phonetypically has sufficient processing power for many of the functions ofthe system to be performed locally, and sufficient storage to capture areasonable amount of data. The amount of storage can also often beexpanded by the user. Phones have reasonably good displays and audiofacilities to provide user feedback, and often a vibrate function fortactile feedback. They also have good power supplies.

Most significantly of all, they are a device that most users are alreadycarrying.

Part III Example Applications of the System

This section lists example uses of the system and applications that maybe built on it. This list is intended to be purely illustrative and inno sense exhaustive.

16. Personal Applications

16.1. Life Library

The Life Library (see also Section 6.1.1) is a digital archive of anyimportant documents that the subscriber wishes to save and is a set ofembodiments of services of this system. Important books, magazinearticles, newspaper clippings, etc., can all be saved in digital form inthe Life Library. Additionally, the subscriber's annotations, comments,and notes can be saved with the documents. The Life Library can beaccessed via the Internet and World Wide Web.

The system creates and manages the Life Library document archive forsubscribers. The subscriber indicates which documents the subscriberwishes to have saved in his life library by scanning information fromthe document or by otherwise indicating to the system that theparticular document is to be added to the subscriber's Life Library. Thescanned information is typically text from the document but can also bea barcode or other code identifying the document. The system accepts thecode and uses it to identify the source document. After the document isidentified the system can store either a copy of the document in theuser's Life Library or a link to a source where the document may beobtained.

One embodiment of the Life Library system can check whether thesubscriber is authorized to obtain the electronic copy. For example, ifa reader scans text or an identifier from a copy of an article in theNew York Times (NYT) so that the article will be added to the reader'sLife Library, the Life Library system will verify with the NYT whetherthe reader is subscribed to the online version of the NYT; if so, thereader gets a copy of the article stored in his Life Library account; ifnot, information identifying the document and how to order it is storedin his Life Library account.

In some embodiments, the system maintains a subscriber profile for eachsubscriber that includes access privilege information. Document accessinformation can be compiled in several ways, two of which are: 1) thesubscriber supplies the document access information to the Life Librarysystem, along with his account names and passwords, etc., or 2) the LifeLibrary service provider queries the publisher with the subscriber'sinformation and the publisher responds by providing access to anelectronic copy if the Life Library subscriber is authorized to accessthe material. If the Life Library subscriber is not authorized to havean electronic copy of the document, the publisher provides a price tothe Life Library service provider, which then provides the customer withthe option to purchase the electronic document. If so, the Life Libraryservice provider either pays the publisher directly and bills the LifeLibrary customer later or the Life Library service provider immediatelybills the customer's credit card for the purchase. The Life Libraryservice provider would get a percentage of the purchase price or a smallfixed fee for facilitating the transaction.

The system can archive the document in the subscriber's personal libraryand/or any other library to which the subscriber has archivalprivileges. For example, as a user scans text from a printed document,the Life Library system can identify the rendered document and itselectronic counterpart. After the source document is identified, theLife Library system might record information about the source documentin the user's personal library and in a group library to which thesubscriber has archival privileges. Group libraries are collaborativearchives such as a document repository for: a group working together ona project, a group of academic researchers, a group web log, etc.

The life library can be organized in many ways: chronologically, bytopic, by level of the subscriber's interest, by type of publication(newspaper, book, magazine, technical paper, etc.), where read, whenread, by ISBN or by Dewey decimal, etc. In one alternative, the systemcan learn classifications based on how other subscribers have classifiedthe same document. The system can suggest classifications to the user orautomatically classify the document for the user.

In various embodiments, annotations may be inserted directly into thedocument or may be maintained in a separate file. For example, when asubscriber scans text from a newspaper article, the article is archivedin his Life Library with the scanned text highlighted. Alternatively,the article is archived in his Life Library along with an associatedannotation file (thus leaving the archived document unmodified).Embodiments of the system can keep a copy of the source document in eachsubscriber's library, a copy in a master library that many subscriberscan access, or link to a copy held by the publisher.

In some embodiments, the Life Library stores only the user'smodifications to the document (e.g., highlights, etc.) and a link to anonline version of the document (stored elsewhere). The system or thesubscriber merges the changes with the document when the subscribersubsequently retrieves the document.

If the annotations are kept in a separate file, the source document andthe annotation file are provided to the subscriber and the subscribercombines them to create a modified document. Alternatively, the systemcombines the two files prior to presenting them to the subscriber. Inanother alternative, the annotation file is an overlay to the documentfile and can be overlaid on the document by software in the subscriber'scomputer.

Subscribers to the Life Library service pay a monthly fee to have thesystem maintain the subscriber's archive. Alternatively, the subscriberpays a small amount (e.g., a micro-payment) for each document stored inthe archive. Alternatively, the subscriber pays to access thesubscriber's archive on a per-access fee. Alternatively, subscribers cancompile libraries and allow others to access the materials/annotationson a revenue share model with the Life Library service provider andcopyright holders. Alternatively, the Life Library service providerreceives a payment from the publisher when the Life Library subscriberorders a document (a revenue share model with the publisher, where theLife Library service provider gets a share of the publisher's revenue).

In some embodiments, the Life Library service provider acts as anintermediary between the subscriber and the copyright holder (orcopyright holder's agent, such as the Copyright Clearance Center, a.k.a.CCC) to facilitate billing and payment for copyrighted materials. TheLife Library service provider uses the subscriber's billing informationand other user account information to provide this intermediationservice. Essentially, the Life Library service provider leverages thepre-existing relationship with the subscriber to enable purchase ofcopyrighted materials on behalf of the subscriber.

In some embodiments, the Life Library system can store excerpts fromdocuments. For example, when a subscriber scans text from a paperdocument, the regions around the scanned text are excerpted and placedin the Life Library, rather than the entire document being archived inthe life library. This is especially advantageous when the document islong because preserving the circumstances of the original scan preventsthe subscriber from re-reading the document to find the interestingportions. Of course, a hyperlink to the entire electronic counterpart ofthe paper document can be included with the excerpt materials.

In some embodiments, the system also stores information about thedocument in the Life Library, such as author, publication title,publication date, publisher, copyright holder (or copyright holder'slicensing agent), ISBN, links to public annotations of the document,readrank, etc. Some of this additional information about the document isa form of paper document metadata. Third parties may create publicannotation files for access by persons other than themselves, such thegeneral public. Linking to a third party's commentary on a document isadvantageous because reading annotation files of other users enhancesthe subscriber's understanding of the document.

In some embodiments, the system archives materials by class. Thisfeature allows a Life Library subscriber to quickly store electroniccounterparts to an entire class of paper documents without access toeach paper document. For example, when the subscriber scans some textfrom a copy of National Geographic magazine, the system provides thesubscriber with the option to archive all back issues of the NationalGeographic. If the subscriber elects to archive all back issues, theLife Library service provider would then verify with the NationalGeographic Society whether the subscriber is authorized to do so. Ifnot, the Life Library service provider can mediate the purchase of theright to archive the National Geographic magazine collection.

16.2. Life Saver

A variation on, or enhancement of, the Life Library concept is the “LifeSaver”, where the system uses the text captured by a user to deduce moreabout their other activities. The scanning of a menu from a particularrestaurant, a program from a particular theater performance, a timetableat a particular railway station, or an article from a local newspaperallows the system to make deductions about the user's location andsocial activities, and could construct an automatic diary for them, forexample as a website. The user would be able to edit and modify thediary, add additional materials such as photographs and, of course, lookagain at the items scanned.

17. Academic Applications

Portable scanners supported by the described system have many compellinguses in the academic setting. They can enhance student/teacherinteraction and augment the learning experience. Among other uses,students can annotate study materials to suit their unique needs;teachers can monitor classroom performance; and teachers canautomatically verify source materials cited in student assignments.

17.1. Children's Books

A child's interaction with a paper document, such as a book, ismonitored by a literacy acquisition system that employs a specific setof embodiments of this system. The child uses a portable scanner thatcommunicates with other elements of the literacy acquisition system. Inaddition to the portable scanner, the literacy acquisition systemincludes a computer having a display and speakers, and a databaseaccessible by the computer. The scanner is coupled with the computer(hardwired, short range RF, etc.). When the child sees an unknown wordin the book, the child scans it with the scanner. In one embodiment, theliteracy acquisition system compares the scanned text with the resourcesin its database to identify the word. The database includes adictionary, thesaurus, and/or multimedia files (e.g., sound, graphics,etc.). After the word has been identified, the system uses the computerspeakers to pronounce the word and its definition to the child. Inanother embodiment, the word and its definition are displayed by theliteracy acquisition system on the computer's monitor. Multimedia filesabout the scanned word can also be played through the computer's monitorand speakers. For example, if a child reading “Goldilocks and the ThreeBears” scanned the word “bear”, the system might pronounce the word“bear” and play a short video about bears on the computer's monitor. Inthis way, the child learns to pronounce the written word and is visuallytaught what the word means via the multimedia presentation.

The literacy acquisition system provides immediate auditory and/orvisual information to enhance the learning process. The child uses thissupplementary information to quickly acquire a deeper understanding ofthe written material. The system can be used to teach beginning readersto read, to help children acquire a larger vocabulary, etc. This systemprovides the child with information about words with which the child isunfamiliar or about which the child wants more information.

17.2. Literacy Acquisition

In some embodiments, the system compiles personal dictionaries. If thereader sees a word that is new, interesting, or particularly useful ortroublesome, the reader saves it (along with its definition) to acomputer file. This computer file becomes the reader's personalizeddictionary. This dictionary is generally smaller in size than a generaldictionary so can be downloaded to a mobile station or associated deviceand thus be available even when the system isn't immediately accessible.In some embodiments, the personal dictionary entries include audio filesto assist with proper word pronunciation and information identifying thepaper document from which the word was scanned.

In some embodiments, the system creates customized spelling andvocabulary tests for students. For example, as a student reads anassignment, the student may scan unfamiliar words with the portablescanner. The system stores a list of all the words that the student hasscanned. Later, the system administers a customized spelling/vocabularytest to the student on an associated monitor (or prints such a test onan associated printer).

17.3. Music Teaching

The arrangement of notes on a musical staff is similar to thearrangement of letters in a line of text. The same scanning devicediscussed for capturing text in this system can be used to capture musicnotation, and an analogous process of constructing a search againstdatabases of known musical pieces would allow the piece from which thecapture occurred to be identified which can then be retrieved, played,or be the basis for some further action.

17.4. Detecting Plagiarism

Teachers can use the system to detect plagiarism or to verify sources byscanning text from student papers and submitting the scanned text to thesystem. For example, a teacher who wishes to verify that a quote in astudent paper came from the source that the student cited can scan aportion of the quote and compare the title of the document identified bythe system with the title of the document cited by the student.Likewise, the system can use scans of text from assignments submitted asthe student's original work to reveal if the text was instead copied.

17.5. Enhanced Textbook

In some embodiments, capturing text from an academic textbook linksstudents or staff to more detailed explanations, further exercises,student and staff discussions about the material, related example pastexam questions, further reading on the subject, recordings of thelectures on the subject, and so forth. (See also Section 7.1.)

17.6. Language Learning

In some embodiments, the system is used to teach foreign languages.Scanning a Spanish word, for example, might cause the word to be readaloud in Spanish along with its definition in English.

The system provides immediate auditory and/or visual information toenhance the new language acquisition process. The reader uses thissupplementary information to acquire quickly a deeper understanding ofthe material. The system can be used to teach beginning students to readforeign languages, to help students acquire a larger vocabulary, etc.The system provides information about foreign words with which thereader is unfamiliar or for which the reader wants more information.

Reader interaction with a paper document, such as a newspaper or book,is monitored by a language skills system. The reader has a portablescanner that communicates with the language skills system. In someembodiments, the language skills system includes a computer having adisplay and speakers, and a database accessible by the computer. Thescanner communicates with the computer (hardwired, short range RF,etc.). When the reader sees an unknown word in an article, the readerscans it with the scanner. The database includes a foreign languagedictionary, thesaurus, and/or multimedia files (sound, graphics, etc.).In one embodiment, the system compares the scanned text with theresources in its database to identify the scanned word. After the wordhas been identified, the system uses the computer speakers to pronouncethe word and its definition to the reader. In some embodiments, the wordand its definition are both displayed on the computer's monitor.Multimedia files about grammar tips related to the scanned word can alsobe played through the computer's monitor and speakers. For example, ifthe words “to speak” are scanned, the system might pronounce the word“hablar,” play a short audio clip that demonstrates the proper Spanishpronunciation, and display a complete list of the various conjugationsof “hablar”. In this way, the student learns to pronounce the writtenword, is visually taught the spelling of the word via the multimediapresentation, and learns how to conjugate the verb. The system can alsopresent grammar tips about the proper usage of “hablar” along withcommon phrases.

In some embodiments, the user scans a word or short phrase from arendered document in a language other than the user's native language(or some other language that the user knows reasonably well). In someembodiments, the system maintains a prioritized list of the user's“preferred” languages. The system identifies the electronic counterpartof the rendered document, and determines the location of the scan withinthe document. The system also identifies a second electronic counterpartof the document that has been translated into one of the user'spreferred languages, and determines the location in the translateddocument corresponding to the location of the scan in the originaldocument. When the corresponding location is not known precisely, thesystem identifies a small region (e.g., a paragraph) that includes thecorresponding location of the scanned location. The correspondingtranslated location is then presented to the user. This provides theuser with a precise translation of the particular usage at the scannedlocation, including any slang or other idiomatic usage that is oftendifficult to accurately translate on a word-by-word basis.

17.7. Gathering Research Materials

A user researching a particular topic may encounter all sorts ofmaterial, both in print and on screen, which they might wish to recordas relevant to the topic in some personal archive. The system wouldenable this process to be automatic as a result of scanning a shortphrase in any piece of material, and could also create a bibliographysuitable for insertion into a publication on the subject.

18. Commercial Applications

Obviously, commercial activities could be made out of almost any processdiscussed in this document, but here we concentrate on a few obviousrevenue streams.

18.1. Fee-Based Searching and Indexing

Conventional Internet search engines typically provide free search ofelectronic documents, and also make no charge to the content providersfor including their content in the index. In some embodiments, thesystem provides for charges to users and/or payments to search enginesand/or content providers in connection with the operation and use of thesystem.

In some embodiments, subscribers to the system's services pay a fee forsearches originating from scans of paper documents. For example, astockbroker may be reading a Wall Street Journal article about a newproduct offered by Company X. By scanning the Company X name from thepaper document and agreeing to pay the necessary fees, the stockbrokeruses the system to search special or proprietary databases to obtainpremium information about the company, such as analyst's reports. Thesystem can also make arrangements to have priority indexing of thedocuments most likely to be read in paper form, for example by makingsure all of the newspapers published on a particular day are indexed andavailable by the time they hit the streets.

Content providers may pay a fee to be associated with certain terms insearch queries submitted from paper documents. For example, in oneembodiment, the system chooses a most preferred content provider basedon additional context about the provider (the context being, in thiscase, that the content provider has paid a fee to be moved up theresults list). In essence, the search provider is adjusting paperdocument search results based on pre-existing financial arrangementswith a content provider. See also the description of keywords and keyphrases in Section 5.2.

Where access to particular content is to be restricted to certain groupsof people (such as clients or employees), such content may be protectedby a firewall and thus not generally indexable by third parties. Thecontent provider may nonetheless wish to provide an index to theprotected content. In such a case, the content provider can pay aservice provider to provide the content provider's index to systemsubscribers. For example, a law firm may index all of a client'sdocuments. The documents are stored behind the law firm's firewall.However, the law firm wants its employees and the client to have accessto the documents through the portable scanner so it provides the index(or a pointer to the index) to the service provider, which in turnsearches the law firm's index when employees or clients of the law firmsubmit paper-scanned search terms via their portable scanners. The lawfirm can provide a list of employees and/or clients to the serviceprovider's system to enable this function or the system can verifyaccess rights by querying the law firm prior to searching the law firm'sindex. Note that in the preceding example, the index provided by the lawfirm is only of that client's documents, not an index of all documentsat the law firm. Thus, the service provider can only grant the lawfirm's clients access to the documents that the law firm indexed for theclient.

There are at least two separate revenue streams that can result fromsearches originating from paper documents: one revenue stream from thesearch function, and another from the content delivery function. Thesearch function revenue can be generated from paid subscriptions fromthe scanner users, but can also be generated on a per-search charge. Thecontent delivery revenue can be shared with the content provider orcopyright holder (the service provider can take a percentage of the saleor a fixed fee, such as a micropayment, for each delivery), but also canbe generated by a “referral” model in which the system gets a fee orpercentage for every item that the subscriber orders from the onlinecatalog and that the system has delivered or contributed to, regardlessof whether the service provider intermediates the transaction. In someembodiments, the system service provider receives revenue for allpurchases that the subscriber made from the content provider, either forsome predetermined period of time or at any subsequent time when apurchase of an identified product is made.

18.2. Catalogs

Consumers may use the portable scanner to make purchases from papercatalogs. The subscriber scans information from the catalog thatidentifies the catalog. This information is text from the catalog, a barcode, or another identifier of the catalog. The subscriber scansinformation identifying the products that s/he wishes to purchase. Thecatalog mailing label may contain a customer identification number thatidentifies the customer to the catalog vendor. If so, the subscriber canalso scan this customer identification number. The system acts as anintermediary between the subscriber and the vendor to facilitate thecatalog purchase by providing the customer's selection and customeridentification number to the vendor.

18.3. Coupons

A consumer scans paper coupons and saves an electronic copy of thecoupon in the scanner, or in a remote device such as a computer, forlater retrieval and use. An advantage of electronic storage is that theconsumer is freed from the burden of carrying paper coupons. A furtheradvantage is that the electronic coupons may be retrieved from anylocation. In some embodiments, the system can track coupon expirationdates, alert the consumer about coupons that will expire soon, and/ordelete expired coupons from storage. An advantage for the issuer of thecoupons is the possibility of receiving more feedback about who is usingthe coupons and when and where they are captured and used.

19. General Applications

19.1. Forms

The system may be used to auto-populate an electronic document thatcorresponds to a paper form. A user scans in some text or a barcode thatuniquely identifies the paper form. The scanner communicates theidentity of the form and information identifying the user to a nearbycomputer. The nearby computer has an Internet connection. The nearbycomputer can access a first database of forms and a second databasehaving information about the user of the scanner (such as a serviceprovider's subscriber information database). The nearby computeraccesses an electronic version of the paper form from the first databaseand auto-populates the fields of the form from the user's informationobtained from the second database. The nearby computer then emails thecompleted form to the intended recipient. Alternatively, the computercould print the completed form on a nearby printer.

Rather than access an external database, in some embodiments, the systemhas a portable scanner that contains the user's information, such as inan identity module, SIM, or security card. The scanner providesinformation identifying the form to the nearby PC. The nearby PCaccesses the electronic form and queries the scanner for any necessaryinformation to fill out the form.

19.2. Business Cards

The system can be used to automatically populate electronic addressbooks or other contact lists from paper documents. For example, uponreceiving a new acquaintance's business card, a user can capture animage of the card with his/her cellular phone. The system will locate anelectronic copy of the card, which can be used to update the cellularphone's onboard address book with the new acquaintance's contactinformation. The electronic copy may contain more information about thenew acquaintance than can be squeezed onto a business card. Further, theonboard address book may also store a link to the electronic copy suchthat any changes to the electronic copy will be automatically updated inthe cell phone's address book. In this example, the business cardoptionally includes a symbol or text that indicates the existence of anelectronic copy. If no electronic copy exists, the cellular phone canuse OCR and knowledge of standard business card formats to fill out anentry in the address book for the new acquaintance. Symbols may also aidin the process of extracting information directly from the image. Forexample, a phone icon next to the phone number on the business card canbe recognized to determine the location of the phone number.

19.3. Proofreading/Editing

The system can enhance the proofreading and editing process. One way thesystem can enhance the editing process is by linking the editor'sinteractions with a paper document to its electronic counterpart. As aneditor reads a paper document and scans various parts of the document,the system will make the appropriate annotations or edits to anelectronic counterpart of the paper document. For example, if the editorscans a portion of text and makes the “new paragraph” control gesturewith the scanner, a computer in communication with the scanner wouldinsert a “new paragraph” break at the location of the scanned text inthe electronic copy of the document.

19.4. Voice Annotation

A user can make voice annotations to a document by scanning a portion oftext from the document and then making a voice recording that isassociated with the scanned text. In some embodiments, the scanner has amicrophone to record the user's verbal annotations. After the verbalannotations are recorded, the system identifies the document from whichthe text was scanned, locates the scanned text within the document, andattaches the voice annotation at that point. In some embodiments, thesystem converts the speech to text and attaches the annotation as atextual comment.

In some embodiments, the system keeps annotations separate from thedocument, with only a reference to the annotation kept with thedocument. The annotations then become an annotation markup layer to thedocument for a specific subscriber or group of users.

In some embodiments, for each capture and associated annotation, thesystem identifies the document, opens it using a software package,scrolls to the location of the scan and plays the voice annotation. Theuser can then interact with a document while referring to voiceannotations, suggested changes or other comments recorded either bythemselves or by somebody else.

19.5. Help in Text

The described system can be used to enhance paper documents withelectronic help menus. In some embodiments, a markup layer associatedwith a paper document contains help menu information for the document.For example, when a user scans text from a certain portion of thedocument, the system checks the markup associated with the document andpresents a help menu to the user. The help menu is presented on adisplay on the scanner or on an associated nearby display.

19.6. Use with Displays

In some situations, it is advantageous to be able to scan informationfrom a television, computer monitor, or other similar display. In someembodiments, the portable scanner is used to scan information fromcomputer monitors and televisions. In some embodiments, the portableoptical scanner has an illumination sensor that is optimized to workwith traditional cathode ray tube (CRT) display techniques such asrasterizing, screen blanking, etc.

A voice capture device which operates by capturing audio of the userreading text from a document will typically work regardless of whetherthat document is on paper, on a display, or on some other medium.

19.6.1. Public Kiosks and Dynamic Session IDs

One use of the direct scanning of displays is the association of devicesas described in Section 15.6. For example, in some embodiments, a publickiosk displays a dynamic session ID on its monitor. The kiosk isconnected to a communication network such as the Internet or a corporateintranet. The session ID changes periodically but at least every timethat the kiosk is used so that a new session ID is displayed to everyuser. To use the kiosk, the subscriber scans in the session ID displayedon the kiosk; by scanning the session ID, the user tells the system thathe wishes to temporarily associate the kiosk with his scanner for thedelivery of content resulting from scans of printed documents or fromthe kiosk screen itself. The scanner may communicate the Session ID andother information authenticating the scanner (such as a serial number,account number, or other identifying information) directly to thesystem. For example, the scanner can communicate directly (where“directly” means without passing the message through the kiosk) with thesystem by sending the session initiation message through the user's cellphone (which is paired with the user's scanner via Bluetooth™).Alternatively, the scanner can establish a wireless link with the kioskand use the kiosk's communication link by transferring the sessioninitiation information to the kiosk (perhaps via short range RF such asBluetooth™, etc.); in response, the kiosk sends the session initiationinformation to the system via its Internet connection.

The system can prevent others from using a device that is alreadyassociated with a scanner during the period (or session) in which thedevice is associated with the scanner. This feature is useful to preventothers from using a public kiosk before another person's session hasended. As an example of this concept related to use of a computer at anInternet café, the user scans a barcode on a monitor of a PC which s/hedesires to use, in response, the system sends a session ID to themonitor that it displays; the user initiates the session by scanning thesession ID from the monitor (or entering it via a keypad or touch screenor microphone on the portable scanner); and the system associates in itsdatabases the session ID with the serial number (or other identifierthat uniquely identifies the user's scanner) of his/her scanner soanother scanner cannot scan the session ID and use the monitor duringhis/her session. The scanner is in communication (through wireless linksuch as Bluetooth™, a hardwired link such as a docking station, etc.)with a PC associated with the monitor or is in direct (i.e., w/o goingthrough the PC) communication with the system via another means such asa cellular phone, etc.

Part IV System Details

Introduction

In some embodiments, the system captures text from a rendered documentand associates some action, data, or functionality with that capture.Section 13 introduced the idea of using supplemental information aboutthe circumstances under which a capture is performed, together withsupplemental information about the user who performed the capture(sometimes collectively called “context”), as well as the data actuallycaptured, to interpret the meaning of the capture and to determine theassociations and actions that should appropriately follow. This is incontrast, for example, to conventional web search engines, whichtypically maintain very little context information from one searchinvocation to another, and know little about the circumstances underwhich the search query was performed.

By considering context, the system can reduce many degrees ofuncertainty in its processes. For example, if the captured data couldhave come from any of several documents, the system can the context todiscard many that would be highly unlikely and help prioritize thosethat remain. Similarly, if the source of a capture is recognized butthere are many actions that the user may wish to take as a result, thecontext can be a valuable aid in deciding which one should be thedefault. The uses to which the system puts context in variousembodiments are discussed in more detail below.

FIG. 4 is a block diagram showing some of the components typicallyincorporated in at least some of the computer systems and other devicesused by the system. These computer systems and devices 400 may includeone or more central processing units (“CPUs”) 401 for executing computerprograms; a computer memory 402 for storing programs and data while theyare being used; a persistent storage device 403, such as a hard drivefor persistently storing programs and data; a computer-readable mediadrive 404, such as a CD-ROM drive, for reading programs and data storedon a computer-readable medium; and a network connection 405 forconnecting the computer system to other computer systems, such as viathe Internet. While computer systems configured as described above aretypically used to support the operation of the system, those skilled inthe art will appreciate that the system may be implemented using devicesof various types and configurations, and having various components.

FIG. 5 is a data flow diagram showing a typical manner in which thesystem uses context information. The system 510 receives a number ofinputs, including the text 521 captured by the user in a captureoperation; supplemental capture information 522 relating to thecircumstances under which the capture operation was performed; andinformation 523 about the user performing the capture. Using theseinputs, the system makes one or more determinations. In someembodiments, the system uses the inputs to determine the document inwhich and the position at which the capture operation was performed 531.In some embodiments, the system uses the inputs to determine whatactions to perform automatically or offer to perform in response to thecapture 532.

User Context

The user context can be summarized as “who, what, when and where,” or asthe four basic factors of identity, activity, time and location. All ofthese factors can profitably be considered as an input to the system.

Identity

In many circumstances, the identity of the user is the most importantpiece of context to a capture, since the system is attempting tooptimize the results for a particular user, based on deductions aboutthat user's real-world activities and thought processes. The useridentity can in some cases be deduced from the identity of the capturedevice, which is owned by or dedicated to him. In other circumstances,the identity of the user can be established, for example, by entering acode or password, by swiping an identity card, or through the use ofbiometric sensors.

The topic of identity also includes personalization—what else is knownabout the user. His specific preferences with regard to the system areof course important, but in some embodiments, the system considers otherinformation. In some embodiments, the system considers otherinformation. Examples are any other accounts the user may hold—forexample with online bookstores—or subscriptions to newspapers.

Time

The time at which a capture occurs is important both in terms of simplelinear time, which may be used to analyze the temporal sequence andproximity of events, and time within a given period, such as the time ofday or the time within the week, which may be used to establishpatterns. A user may habitually read a newspaper on the train on the wayto work, for example, and a novel on the way home.

The use of timestamps in relation to other events, and the concept of ahistory of capture contexts, is discussed in more detail below.

Location

A user who is in a particular city is more likely to be reading anewspaper local to that city. A user who is in a library is probablyreading something that is listed in that library's catalog. Thegeographical location of the capture, therefore, can be very important,and while this is often expressed in terms of latitude and longitude,other means of describing it can also be useful. Examples includeproximity to some entity or type of entity—“the user is in arestaurant”—or the location in terms of some other infrastructure, suchas a network—“the user is connected via this wireless endpoint” or “theuser's phone is in range of this cellular base station.”

In some embodiments, the system determines the location in terms asgeneral as “indoors” or “outdoors,” which may be deduced from the lightentering the sensor of an optical capture device. Similarly the systemmay deduce “on a train” or “in a quiet room” from the ambient noise ofan audio capture device.

Activity

The user's activity includes his interactions with the system, and theanswer to such questions as: What else has the user captured? What didhe do last time this situation occurred? What was he doing at the timeof making this capture? But the user's “activity” is by no means limitedto his use of the system. Other examples of useful activity includeinteractions with digital documents, with search engines, with printers,and with other users, for example by means of phones, email, instantmessaging, particularly when those communications involve transmissionof or references to documents.

Immediate Capture Context

The capture device is primarily intended to capture text or symbols fromthe rendered document. In some embodiments the capture device is able tocapture information that is supplemental and can provide valuablecontext. Examples include the font in which the text is printed, thecolors of the text and the background, the location of line breaks, andthe proximity of the edge of a column or the edge of a page. In someembodiments, the capture device is also able to pick up more detailabout the physical nature of the rendered document; for example, that itis printed on glossy or matte paper, that the paper has a watermark,that it was printed with a high- or low-resolution printer. A scan fromglossy paper, for example, is unlikely to be from a newspaper article.

In some embodiments, the scanning device is able to scan from anelectronic display as well as from a printed document. These differentmodes of use can be identified, and similar characteristics noted fordisplays as for printed documents. Examples of such characteristicsinclude resolution, quality of display, and refresh rate.

In situations where such characteristics are not directly useful indetermining system operation, the changes in the characteristics canstill be of interest. For example, it may not be possible to deducedirectly very much about the origin of a document from the nature of theprinting, but if it is clear that the text in two successive scans camefrom two different printers, it is highly unlikely that they originatefrom the same document.

Document Location Context

Another type of capture context used by the system in some embodimentsis the location of the capture within the rendered document. Importantfactors include whether the capture came from the beginning of thedocument or the end, the top, middle or bottom of a page, a sidebar,footnote or endnote, and the proximity to items such as pictures,tables, advertisements, and quotations. Such factors may be consideredanalogies in the Capture Context to geographical location in the UserContext.

Other Device Capabilities

In some embodiments, sensors in the capture device can detect otheraspects of the capture environment. For example, the nature of theambient light—is it daylight, tungsten filament, or a fluorescentsource? In the case of audio capture, the system can deduce informationfrom the background noise or from the speech patterns of the userreading the text. As has been mentioned in section 6.2.2, the capturesensor may be used to identify the user, for example as a biometricsensor by scanning the fingerprint.

The capture device may include other sensors, which can provide furtherinformation about its environment. Examples include GPS receivers, RFIDtags, temperature sensors, wireless network interfaces. When the devicedoes not directly include such facilities, it may be able to communicatewith other devices that do.

Connectivity

The degree of connectivity of the capture device can affect many aspectsof the system. Whether the device is “online,” “offline” or somewherein-between can affect the confidence with which the captured documentcan be identified, the options available to the user, the statisticsavailable from the rest of the system, to name just a few factors.

Other Captures

The broader capture context includes the documents or types of documentsrecently, or typically, scanned by a user. As an example, the system maydeduce that one user only ever captures text from novels, while anotheronly captures from recent newspaper editions. Similarly, one user mayhave the habit of scanning titles, headings and authors, where anotheris more likely to capture bibliographic cross-references. Suchinformation can be useful in interpreting any particular capture.

Other Aspects & Extra Dimensions

Time

Most of the above factors have been described in terms of the immediatecontext: the status at the time of the capture. In some embodiments, thesystem adds an extra dimension of time. Most of the contextual factorsdescribed above may be offset in time from the actual capture. Forexample, it is unlikely that a user would be scanning a document whilecomposing an email to somebody, but the fact that a user sends adocument to somebody shortly after a capture may be a strong hint as tothe identity of the document.

A significant part of the context of any capture is the details of anycaptures that came before it and the captures that will come after, bothin terms of the context in which they occurred, the data that wasactually captured, and any actions that occurred as a result. In someembodiments, it is unusual that any capture will be examined in completeisolation.

The most obvious example is that two captures within a few seconds ofeach other are very likely to come from the same document. What is more,the second capture is probably from later in the document than the firstone because users tend to read from beginning to end. Two captures whichare several days apart are much less likely to be from the samedocument, especially if that document is a short one.

Similarly, if an examination of a user's capture history indicates thathe typically reads the New York Times between 7 am and 9 am eachmorning, then the likelihood is much greater that any new capture madeduring that period came from that source.

In some embodiments, the system distinguishes between the context at thetime the capture occurred and the context now. In some cases, all of theinteractions with the system will take place at the time the captureoccurs. In other circumstances, system operations may be performed at adifferent time from the capture. This may occur, for example, where thecapture device has no connectivity at the time of capture, or when theuser returns to examine earlier captures logged in the user's LifeLibrary Archive as described in Section 6.1. In such cases, the systemeither selects the capture time or the processing time as the time mostrelevant to the capture, or considers both times.

In some embodiments, the system also considers the future in itsanalysis. There are two senses in which this may occur: 1) The systempredicts the context in which the user will shortly find himself. Forexample, it may be more likely that the user is reading a book about aparticular city not because he is in that city, but because he is on aplane heading towards it. Similarly, a user is more likely to bescanning a document by or about a particular person if his scheduleindicates that he has a meeting with that person shortly. 2) The systemor the user may be examining or interacting with a capture event fromthe past, and so can interpret that event in the light of things thathappened afterwards. Thus the system might make a deduction that acertain capture was from the Seattle Times because the capture thatfollowed it was from the menu of a Seattle restaurant.

In some embodiments, the system also proactively informs the user ifinformation that the system receives affects the way past captures couldbe interpreted.

The Device and the User

In some embodiments, the system assumes that the context of the deviceand the context of the user are the same. This is often, but not always,the case. In some embodiments, the user may use multiple devices, and inothers multiple users may use a single device, such as where the deviceis tethered and in a public place such as a store or a library. Asdiscussed above, it may be necessary to establish the identity of theuser separately from that of the device.

Use of the System to Establish Context

While much of the foregoing discussion is focused on the use of contextto influence the operation of the system, there are many situations inwhich the use of the system can also help to establish the context.

To take the example of geographical location, it can be useful toestablish the location of a user by means independent of documentidentification performed by the system, such as by using a GPS receiveror the location of a wireless network to which the user is connected. Inthe absence of such direct information, however, some embodiments deducethe geographical context from the use of the system. Thus, the times ofday at which the system is used are an important clue as to the timezone in which the user is located. In some embodiments, the system alsoconsiders the capture of information in a particular language or from adocument likely to be very locally-targeted, such as a local newspaper,a public transport timetable, a restaurant menu.

Such indications are not always completely reliable—for example, theuser may have taken the restaurant menu home with him. Despite this, theconsideration of such indications in probabilistic analysis can be veryuseful. In some embodiments, the system performs filtering to removerogue indications. If the system has a strong indication that a user isin London, for example, the system ascribes a low likelihood of accuracyto any suggestion that he is in San Francisco two hours later.

The Other Users

In some embodiments, the system also makes use of the information aboutthe activities and context of other users, especially as they relate tothe capture at hand, such as by being relevant to the user's location orthe document being scanned. That is, the system can make use of conceptssuch as:

“Other people in Boston are reading this book at the moment,” or

“This magazine article has been very popular in the last week,” or

“Users who also read that review often went on to scan passages fromthis book.”

Making Use of Context

Many aspects of the system benefit from the availability of contextinformation.

Operation of the system typically begins with the capture of some datafrom the rendered document, and the use of that data to identify anelectronic counterpart to the rendered document. An example is scanninga few words from a rendered document and using them to find theelectronic original from which the document was printed. Often, thenumber of words required to uniquely identify a document is small, butsometimes the same phrase may occur in several documents and the resultsof the identification are ambiguous. It is then that context informationcan be brought to bear.

For example, if the same phrase occurs in a recent edition of theWashington Post and also in the Times of India, but the user is known tobe in North America, the Washington Post article is much more likely tobe the correct one. If the article occurred in the Washington Postwithin the last few days, and the candidate from the Times of India wasfrom 18 months ago, then the probability of the Washington Post beingthe source again rises substantially. Lastly, if it is also known thatthe user has captured several articles from the Washington Post in thepast but has never captured anything from the Times of India, then thesystem can be almost certain that the former is the correct source, andcan act accordingly.

In this example, if each bit of contextual knowledge increases theprobability that the capture came from the Washington Post by a factorof ten—probably a rather conservative estimate for these examples—thecombination of the three increases by a factor of 1000 the probabilitythat a system which incorporates them, and thus presents options to theuser based on the origin being the Washington Post, will be making acorrect decision on behalf of the user when compared to a system whichignores such factors.

A second example of the use of context to identify the electroniccounterpart of a document comes from deducing that two or more capturesprobably came from the same document. The system may do this byobserving that they were close together in time, that they captured textin the same language, color, or font, or from the same type of paper, orany combination of these and similar factors.

Without taking context into account, the accuracy with which a documentcan be identified depends on the amount of text captured and thecontents of that text. In an example experiment, the following tablelists the number of documents containing the specified phrases asreported by the Google search engine:

TABLE 1 Phrase Approx number of hits “on a dark” 220,000 “on a darkevening” 1,030 “on a dark evening when” 15 “on a dark evening when she”1

Thus in many cases, without the use of context, the system can identifythe document uniquely simply by requiring the user to capture along-enough phrase. This may be inconvenient, however, since in somecases the length of phrase required may run to more than canconveniently be captured in a single scan. In addition, the user may becapturing several phrases from a document to indicate his interest inthem, and those phrases may often be quite short. Longer passages, aswell as being inconvenient to capture, may not identify the topic ofinterest as clearly as the short phrases.

In some embodiments, the system uses contextual information to deducethat two successive captures came from the same document, for examplebecause they occur very close together in time. This may allow theidentification of the document based on combinations of shorter phrases.The same unique document identified in Table 1 above, for example, maybe identified by two much shorter phrases occurring separately in thedocument:

TABLE 2 Phrase Number of hits “nokia 3310” 676,000 “a dark, evening” 750“a dark evening” and “nokia 3310” 1

It will also be apparent that once the context of the scan has beenestablished in this way, there can be no doubt about the source of anyadditional captures from the same document, even if they are singlewords, except where those words occur more than once in that document.Even then, a great deal can be deduced from the order in which thecaptures occur, as words which are captured later are likely to occurlater in the document.

In some embodiments, the capture process is less precise—for example,due to the possibility of recognition errors—or the search process lessexact. The establishment of the electronic counterpart then becomes amatter of pure statistical probabilities rather than being partiallybased on the exact matching of a search pattern. In some suchembodiments, the system considers contextual factors to help improve thestatistical certainty at all stages of this process. The system, forexample, is informed to consider both the French and the Englishdictionaries if the English-speaking user is known to be in France.

Tailoring the Content and Activities Available to a User

In some embodiments, the system also uses context to select the contentand the options available to the user of a system.

As an example, a user capturing some text from a book may, as a resultof markup associated with that book, be offered the option to purchase acopy of the book from an online retailer. If the system can determine,through examining his previous captures, that the user is a regularreader of a particular publication, it may offer him a special discountprice available to subscribers of that publication. If, on the otherhand, the system can determine that the user is in a country to whichthe retailer has no shipping facilities, the system need not offer himthe option of purchasing from that retailer.

In some embodiments, the system achieves such control through the use ofcontext conditions included in the markup that must be met for themarkup to be valid or relevant. A review of a theater performance, forexample, may have markup associated with it which causes the system tooffer the user a link to a web site selling tickets to the play. Thismarkup may have an associated context condition which specifies that thelink is to be offered only before Jun. 30, 2005, the date at which theperformances cease, since offering this option to the user after thistime would be unhelpful.

Similarly, in certain contexts, the system restricts the range ofactivities available to a particular user for security or other similarreasons. An example is in the use of the system as a copying device. Auser may carry a scanning device that enables him to capture phrasesfrom documents and also store electronic copies of the documentscontaining the captures. In some environments where copying of the datais restricted, for example in secure military establishments, the systemrestricts or disallows use of the device based upon contextualinformation. In some embodiments, the scanner device is designed tooperate in daylight or under conventional electric light; fluorescentlighting of a particular frequency is installed in situations whereoperation of the scanner device is not allowed; and the device refusesto function under such lighting conditions.

Tailoring the Presentation of the System

Another way that the system uses context is to present system output ina way that is most appropriate for the user's activities and situation.At the level of the immediate capture context, in some embodiments, thesystem does little more than prompt the user to resolve ambiguitiesabout documents using a menu that is ordered based on his recent use ofdocuments. At the level of the user context, in some embodiments, acapture device that is integrated with a mobile phone detects that auser is traveling in a car and prompts him—using voice prompts as wellas graphical menus—to reduce distraction in the event that he isdriving.

In some embodiments, the system provides direct feedback to the userabout the state of the context analysis process. For example, the devicecan provide an indication that it has concluded that the user is in thesame document as the previous capture, or that it has gathered enoughinformation to be certain of the current capture context.

Proactive Prediction

In some embodiments, the system predicts a change of context in thefuture, typically by the use of past and present context. For example,in some embodiments, capture devices have substantial caching facilitiesto improve their performance in general and to allow them to functionusefully when offline (see section 15.3). For such devices, the user'scontext is an important input in the decision about what to cache andwhen. A user who habitually reads the paper on the 7:30 train to work islikely to appreciate a system that has pre-cached the index for thatday's paper before he starts the journey. A user who has spent an hourin the departure lounge of an international airport is likely to beoffline for some hours and would benefit from the cache being updatedbefore the flight. This user is also less likely to be capturinginformation from the local newspaper for the next few days, thusallowing space used by indices from that paper to be freed up.

Implementation Examples

As a simple example implementation, this section considers the use ofcontext to prioritize and disambiguate documents in the case where acapture may have occurred from more than one source.

Use of Context in the Selection of Candidates

In a traditional text-based query, which is used to search for matchingdocuments in a corpus, there may be many candidate documents thatcontain the query terms (the words or phrases used in the search). Insome embodiments, there can be uncertainty about the precision of thetext recognition process, meaning that there may be extra candidatewords in the query with associated probabilities of accuracy, alsoadding to the numbers of candidate matching documents. These candidatesmay be considered to be located in a multi-dimensional search “space.”The dimensions of the space are based on the query terms used. Thesystem uses the proximity in this space of each of the candidatedocuments to the query to prioritize the search results and identify themost likely candidates. The system bases the scaling of the dimensions,the weighting of the terms and the method of calculating proximity onsuch factors as the frequency of the terms in the normal use of thelanguage and their frequency in the candidate document relative to thesize of the document.

In some embodiments, the system uses context as an extra set ofdimensions in this space. As an example, the system may use the factthat a document that has been recently scanned is more likely to be thesource of the current scan, especially if the scan is within the lastfew minutes. The system therefore positions each candidate document inthe time dimension based on the closest time a capture was made from it.The system positions the query (associated with the “current” capture)based on the time at which the capture occurred. The system places anydocuments from which a capture has never been made or for which thatcapture was more than X hours from the time of the current capture inthe space at a distance of X hours away from the current capture. Thus,the system will consider any documents from which a capture has beenmade within X hours of the current capture more likely candidates thanthe others, and, all other factors being equal, will consider thoseclosest in time the most likely.

In some embodiments, the system constructs a similar dimension for “timeof day,” where positioning in that dimension is based on the time withinthe 24-hour clock at which captures occur. Thus, documents that arehabitually scanned between 8 and 9 a.m. are more likely to be recognizedas matches for other scans occurring in that period.

In some cases the distance metric in a particular dimension will bespecific to that dimension. In some dimensions they will be non-linear.In the “time of day” example they may need to wrap around so that23:59:59 (pm) is very close to 00:00:00 (am).

Context as a Second Stage

In some embodiments, the system identifies candidate documents basedupon which documents match or fail to match the captured text. Thesystem automatically excludes documents that fail to match. In thiscase, the system uses context to prioritize the documents after it hasidentified the matching candidates.

The Use of Document Type

In some embodiments, the system considers documents based upon theirtype. For example, if a capture made late at night produces twocandidate source documents, one of which is a novel and the other a TVguide, and the system knows that previous captures by the user at thattime of night have always been from novels, then the system gives thenovel a higher priority. In some embodiments, the system considersproximity to documents of a similar type, such as by using standardclustering techniques.

Conclusion

It will be appreciated by those skilled in the art that theabove-described system may be straightforwardly adapted or extended invarious ways. While the foregoing description makes reference toparticular embodiments, the scope of the invention is defined solely bythe claims that follow and the elements recited therein.

We claim:
 1. A method comprising: receiving, at a computing device, textcaptured from a rendered document during a text capture operation;receiving, at the computing device, supplemental information relating tocircumstances under which the text capture operation was performed, thesupplemental information comprising information indicating ageographical location at which the text capture operation occurs, theinformation indicating a geographical location at which the text captureoperation occurs comprising information indicating a location as beingindoors or outdoors; and determining, by the computing device and basedon the captured text and the supplemental information, an action to beperformed; wherein a determination of the location as being indoors oroutdoors is based on light entering a sensor of an optical capturedevice.
 2. The method of claim 1, wherein determining the action to beperformed comprises determining to discard at least one document fromamong a plurality of documents identified as having the captured text.3. The method of claim 2, wherein determining the action to be performedfurther comprises determining to prioritize any documents of theplurality of documents remaining after discarding the at least onedocument.
 4. The method of claim 1, wherein determining the action to beperformed comprises determining to select a default action to performfrom among a plurality of actions.
 5. The method of claim 1, wherein theinformation indicating a geographical location at which the text captureoperation occurs comprises information expressed in terms of latitudeand longitude.
 6. The method of claim 1, further comprising: predicting,by the computing device, context with respect to a user of a capturedevice that performs the text capture operation, wherein at least aportion of the supplemental information is based on the predictedcontext.
 7. The method of claim 6, wherein the predicted context isbased on information indicating the user is on an airplane being flownto a particular city.
 8. A method comprising: receiving, at a computingdevice, text captured from a rendered document during a text captureoperation; receiving, at the computing device, supplemental informationrelating to circumstances under which the text capture operation wasperformed, the supplemental information comprising informationindicating a geographical location at which the text capture operationoccurs; and determining, by the computing device and based on thecaptured text and the supplemental information, an action to beperformed; wherein the information indicating a geographical location atwhich the text capture operation occurs comprises information indicatinga location deduced from an ambient noise of an audio capture device thatperforms the text capture operation.
 9. A method comprising: receiving,at a computing device, text captured from a rendered document during atext capture operation; receiving, at the computing device, supplementalinformation relating to circumstances under which the text captureoperation was performed; predicting, by the computing device, contextwith respect to a user of a capture device that performs the textcapture operation, wherein at least a portion of the supplementalinformation is based on the predicted context; and determining, by thecomputing device and based on the captured text and the supplementalinformation, an action to be performed; wherein the predicted context isbased on information indicating the user is on an airplane being flownto a particular city; and wherein the predicted context indicates theuser is reading a document about the particular city.
 10. A methodcomprising: receiving, at a computing device, text captured from arendered document during a text capture operation; receiving, at thecomputing device, supplemental information relating to circumstancesunder which the text capture operation was performed; predicting, by thecomputing device, context with respect to a user of a capture devicethat performs the text capture operation, wherein at least a portion ofthe supplemental information is based on the predicted context; anddetermining, by the computing device and based on the captured text andthe supplemental information, an action to be performed; wherein thepredicted context is based on schedule information indicating the useris meeting with a particular person.
 11. The method of claim 10, whereinthe predicted context indicates the user is reading a document by orabout the particular person.
 12. A system comprising: an input receiveroperable to receive text captured from a rendered document during a textcapture operation, and supplemental information relating tocircumstances of performing the text capture operation, the supplementalinformation comprising information indicating a geographical location atwhich the text capture operation occurs, the information indicating ageographical location at which the text capture operation occurscomprising information indicating a location as being indoors oroutdoors; a processing unit; and a computer memory configured to storethe captured text, the supplemental information, and computer-readableprograms executable by the processing unit; wherein thecomputer-readable program instructions are executable by the processingunit to determine, based on the captured text and the supplementalinformation, an action to be performed; and wherein a determination ofthe location as being indoors or outdoors is based on light entering asensor of an optical capture device.
 13. The system of claim 12, whereinthe input receiver comprises a network connection that connects thesystem to the Internet.
 14. The system of claim 12, wherein thecomputer-readable program instructions are executable by the processingunit to perform the determined action.
 15. The system of claim 12,wherein the computer-readable program instructions are executable by theprocessing unit to predict context with respect to a user of a capturedevice that performs the text capture operation, and wherein at least aportion of the supplemental information is based on the predictedcontext.
 16. A non-transitory computer readable medium having storedtherein instructions, that when executed by a computing device, causethe computing device to perform functions comprising: receiving, at acomputing device, text captured from a rendered document during a textcapture operation; receiving, at the computing device, supplementalinformation relating to circumstances under which the text captureoperation was performed, the supplemental information comprisinginformation indicating a geographical location at which the text captureoperation occurs, the information indicating a geographical location atwhich the text capture operation occurs comprising informationindicating a location as being indoors or outdoors; and determining, bythe computing device and based on the captured text and the supplementalinformation, an action to be performed; wherein a determination of thelocation as being indoors or outdoors is based on light entering asensor of an optical capture device.
 17. The non-transitory computerreadable medium of claim 16, wherein the stored instructions, whenexecuted by the computing device, further cause performance of thedetermined action.
 18. The non-transitory computer readable medium ofclaim 16, wherein the stored instructions, when executed by thecomputing device, further cause the computing device to predict contextwith respect to a user of a capture device that performs the textcapture operation, and wherein at least a portion of the supplementalinformation is based on the predicted context.